Methods and systems for authentication of an electric aircraft for recharging

ABSTRACT

A method for authentication of an electric aircraft for recharging. The method includes receiving, at a charging connector, an authentication datum from an electric aircraft. The charging connector is configured to mate with an electric aircraft port of the electric aircraft. The method further includes verifying, at a computing device communicatively connected to the charging connector, the authentication datum. The method further includes enabling charging of the electric aircraft, at the charging connector and by the computing device, as a function of the verification of the authentication datum. A system for authentication of an electric aircraft for recharging is also provided.

FIELD OF THE INVENTION

The present invention generally relates to the field of electric aircraft. In particular, the present invention is directed to methods and systems for authentication of an electric aircraft for recharging.

BACKGROUND

Authentication of identity associated with aircraft may be required in many air traffic control scenarios and at many airports, landing and refueling sites. Effectively and accurately verifying such an identity for numerous aircraft can be a difficult task and can pose technical challenges.

SUMMARY OF THE DISCLOSURE

In an aspect a method for authentication of an electric aircraft for recharging is provided. The method includes receiving, at a charging connector, an authentication datum from an electric aircraft. The charging connector is configured to mate with an electric aircraft port of the electric aircraft. The method further includes verifying, at a computing device communicatively connected to the charging connector, the authentication datum. The method further includes enabling charging of the electric aircraft, at the charging connector and by the computing device, as a function of the verification of the authentication datum.

In another aspect a system for authentication of an electric aircraft for recharging is provided. The system includes a charging connector and a computing device. The charging connector is configured to receive an authentication datum from an electric aircraft, and mate with an electric aircraft port of the electric aircraft. The computing device is communicatively connected to the charging connector. The computing device is configured to verify the authentication datum, and enable, at the charging connector, charging of the electric aircraft as a function of the verification of the authentication datum.

These and other aspects and features of non-limiting embodiments of the present invention will become apparent to those skilled in the art upon review of the following description of specific non-limiting embodiments of the invention in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of illustrating the invention, the drawings show aspects of one or more embodiments of the invention. However, it should be understood that the present invention is not limited to the precise arrangements and instrumentalities shown in the drawings, wherein:

FIG. 1A is a block diagram of an exemplary embodiment of a system for authentication of an electric aircraft for recharging;

FIG. 1B is a simplified schematic diagram of an exemplary embodiment of an immutable sequential listing;

FIG. 2 is a diagrammatic representation of an exemplary embodiment of an electric aircraft;

FIG. 3 is a block diagram of an exemplary embodiment of a flight controller;

FIG. 4 is a block diagram of an exemplary embodiment of a machine-learning module;

FIG. 5 is a block diagram of an exemplary embodiment of a method for authentication of an electric aircraft for recharging; and FIG. 6 is a block diagram of a computing system that can be used to implement any one or more of the methodologies disclosed herein and any one or more portions thereof.

The drawings are not necessarily to scale and may be illustrated by phantom lines, diagrammatic representations and fragmentary views. In certain instances, details that are not necessary for an understanding of the embodiments or that render other details difficult to perceive may have been omitted.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, that the present invention may be practiced without these specific details. As used herein, the word “exemplary” or “illustrative” means “serving as an example, instance, or illustration.” Any implementation described herein as “exemplary” or “illustrative” is not necessarily to be construed as preferred or advantageous over other implementations. All of the implementations described below are exemplary implementations provided to enable persons skilled in the art to make or use the embodiments of the disclosure and are not intended to limit the scope of the disclosure, which is defined by the claims. For purposes of description herein, the terms “upper”, “lower”, “left”, “rear”, “right”, “front”, “vertical”, “horizontal”, “upward”, “downward”, “forward”, “backward” and derivatives thereof shall relate to the orientation in FIG. 2. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the following detailed description. It is also to be understood that the specific devices and processes illustrated in the attached drawings, and described in the following specification, are simply exemplary embodiments of the inventive concepts defined in the appended claims. Hence, specific dimensions and other physical characteristics relating to the embodiments disclosed herein are not to be considered as limiting, unless the claims expressly state otherwise.

At a high level, aspects of the present disclosure are directed to systems and methods for authentication of an electric aircraft for recharging. In an embodiment, a charging connector and a computing device, communicatively connected to the charging connector are used to implement authentication of electric aircraft for charging or recharging. Aspects of the present disclosure can be used to authenticate an identity associated with electric aircraft for access to charging or recharging facilities. Aspects of the present disclosure can also be used to verify or confirm electric aircraft's authorization to avail the facilities of a particular recharging structure or station. This is so, at least in part, because charging connector can be configured to enable or disable flow of charging current therethrough to electric aircraft. Advantageously, aspects of the present disclosure allow for an enhanced level of logistical safety by permitting authorized or suitable electric aircraft to be provided with appropriate charging services.

In some instances, authentication of electric aircraft at charging (or recharging) may be implemented once it is plugged into charging station, for example and without limitation, a helideck, a standalone charger, or the like, among others. In other embodiments, authentication may be performed by using a wireless connection. Any suitable authentication means may be used, such as and without limitation, verification of aircraft VIN (vehicle identification number), blockchain authentication (charger could be public/private key), and the like, among others. It could be desired, or needed, that only appropriate and/or authorized electric aircraft are able to be charged (or recharged) at a particular charging station or site. For instance, and without limitation, authentication may include verification that an aircraft is part of a fleet (e.g. fleet membership), verification that an aircraft is recharging at its scheduled appointment time, verification of other credentials such as radio frequency identification (RFID), and the like, among others. Exemplary embodiments illustrating aspects of the present disclosure are described below in the context of several specific examples.

In an embodiment, methods and systems described herein may perform or implement one or more aspects of a cryptographic system. In one embodiment, a cryptographic system is a system that converts data from a first form, known as “plaintext,” which is intelligible when viewed in its intended format, into a second form, known as “ciphertext,” which is not intelligible when viewed in the same way. Ciphertext may be unintelligible in any format unless first converted back to plaintext. In one embodiment, a process of converting plaintext into ciphertext is known as “encryption.” Encryption process may involve the use of a datum, known as an “encryption key,” to alter plaintext. Cryptographic system may also convert ciphertext back into plaintext, which is a process known as “decryption.” Decryption process may involve the use of a datum, known as a “decryption key,” to return the ciphertext to its original plaintext form. In embodiments of cryptographic systems that are “symmetric,” decryption key is essentially the same as encryption key: possession of either key makes it possible to deduce the other key quickly without further secret knowledge. Encryption and decryption keys in symmetric cryptographic systems may be kept secret and shared only with persons or entities that the user of the cryptographic system wishes to be able to decrypt the ciphertext. One example of a symmetric cryptographic system is the Advanced Encryption Standard (“AES”), which arranges plaintext into matrices and then modifies the matrices through repeated permutations and arithmetic operations with an encryption key.

In embodiments of cryptographic systems that are “asymmetric,” either encryption or decryption key cannot be readily deduced without additional secret knowledge, even given the possession of a corresponding decryption or encryption key, respectively; a common example is a “public key cryptographic system,” in which possession of the encryption key does not make it practically feasible to deduce the decryption key, so that the encryption key may safely be made available to the public. An example of a public key cryptographic system is RSA, in which an encryption key involves the use of numbers that are products of very large prime numbers, but a decryption key involves the use of those very large prime numbers, such that deducing the decryption key from the encryption key requires the practically infeasible task of computing the prime factors of a number which is the product of two very large prime numbers. Another example is elliptic curve cryptography, which relies on the fact that given two points P and Q on an elliptic curve over a finite field, and a definition for addition where A+B=−R, the point where a line connecting point A and point B intersects the elliptic curve, where “0,” the identity, is a point at infinity in a projective plane containing the elliptic curve, finding a number k such that adding P to itself k times results in Q is computationally impractical, given correctly selected elliptic curve, finite field, and P and Q.

In some embodiments, systems and methods described herein produce cryptographic hashes, also referred to by the equivalent shorthand term “hashes.” A cryptographic hash, as used herein, is a mathematical representation of a lot of data, such as files or blocks in a block chain as described in further detail below; the mathematical representation is produced by a lossy “one-way” algorithm known as a “hashing algorithm.” Hashing algorithm may be a repeatable process; that is, identical lots of data may produce identical hashes each time they are subjected to a particular hashing algorithm. Because hashing algorithm is a one-way function, it may be impossible to reconstruct a lot of data from a hash produced from the lot of data using the hashing algorithm. In the case of some hashing algorithms, reconstructing the full lot of data from the corresponding hash using a partial set of data from the full lot of data may be possible only by repeatedly guessing at the remaining data and repeating the hashing algorithm; it is thus computationally difficult if not infeasible for a single computer to produce the lot of data, as the statistical likelihood of correctly guessing the missing data may be extremely low. However, the statistical likelihood of a computer of a set of computers simultaneously attempting to guess the missing data within a useful timeframe may be higher, permitting mining protocols as described in further detail below.

In an embodiment, hashing algorithm may demonstrate an “avalanche effect,” whereby even extremely small changes to lot of data produce drastically different hashes. This may thwart attempts to avoid the computational work necessary to recreate a hash by simply inserting a fraudulent datum in data lot, enabling the use of hashing algorithms for “tamper-proofing” data such as data contained in an immutable ledger as described in further detail below. This avalanche or “cascade” effect may be evinced by various hashing processes; persons skilled in the art, upon reading the entirety of this disclosure, will be aware of various suitable hashing algorithms for purposes described herein. Verification of a hash corresponding to a lot of data may be performed by running the lot of data through a hashing algorithm used to produce the hash. Such verification may be computationally expensive, albeit feasible, potentially adding up to significant processing delays where repeated hashing, or hashing of large quantities of data, is required, for instance as described in further detail below. Examples of hashing programs include, without limitation, SHA256, a NIST standard; further current and past hashing algorithms include Winternitz hashing algorithms, various generations of Secure Hash Algorithm (including “SHA-1,” “SHA-2,” and “SHA-3”), “Message Digest” family hashes such as “MD4,” “MD5,” “MD6,” and “RIPEMD,” Keccak, “BLAKE” hashes and progeny (e.g., “BLAKE2,” “BLAKE-256,” “BLAKE-512,” and the like), Message Authentication Code (“MAC”)-family hash functions such as PMAC, OMAC, VMAC, HMAC, and UMAC, Poly1305-AES, Elliptic Curve Only Hash (“ECOH”) and similar hash functions, Fast-Syndrome-based (FSB) hash functions, GOST hash functions, the Grøstl hash function, the HAS-160 hash function, the JH hash function, the RadioGatún hash function, the Skein hash function, the Streebog hash function, the SWIFFT hash function, the Tiger hash function, the Whirlpool hash function, or any hash function that satisfies, at the time of implementation, the requirements that a cryptographic hash be deterministic, infeasible to reverse-hash, infeasible to find collisions, and have the property that small changes to an original message to be hashed will change the resulting hash so extensively that the original hash and the new hash appear uncorrelated to each other. A degree of security of a hash function in practice may depend both on the hash function itself and on characteristics of the message and/or digest used in the hash function. For example, where a message is random, for a hash function that fulfills collision-resistance requirements, a brute-force or “birthday attack” may to detect collision may be on the order of O(2^(n/2)) for n output bits; thus, it may take on the order of 2²⁵⁶ operations to locate a collision in a 512 bit output “Dictionary” attacks on hashes likely to have been generated from a non-random original text can have a lower computational complexity, because the space of entries they are guessing is far smaller than the space containing all random permutations of bits. However, the space of possible messages may be augmented by increasing the length or potential length of a possible message, or by implementing a protocol whereby one or more randomly selected strings or sets of data are added to the message, rendering a dictionary attack significantly less effective.

Embodiments described in this disclosure may perform secure proofs. A “secure proof,” as used in this disclosure, is a protocol whereby an output is generated that demonstrates possession of a secret, such as device-specific secret, without demonstrating the entirety of the device-specific secret; in other words, a secure proof by itself, is insufficient to reconstruct the entire device-specific secret, enabling the production of at least another secure proof using at least a device-specific secret. A secure proof may be referred to as a “proof of possession” or “proof of knowledge” of a secret. Where at least a device-specific secret is a plurality of secrets, such as a plurality of challenge-response pairs, a secure proof may include an output that reveals the entirety of one of the plurality of secrets, but not all of the plurality of secrets; for instance, secure proof may be a response contained in one challenge-response pair. In an embodiment, proof may not be secure; in other words, proof may include a one-time revelation of at least a device-specific secret, for instance as used in a single challenge-response exchange.

Secure proof may include a zero-knowledge proof, which may provide an output demonstrating possession of a secret while revealing none of the secret to a recipient of the output; zero-knowledge proof may be information-theoretically secure, meaning that an entity with infinite computing power would be unable to determine secret from output. Alternatively, zero-knowledge proof may be computationally secure, meaning that determination of secret from output is computationally infeasible, for instance to the same extent that determination of a private key from a public key in a public key cryptographic system is computationally infeasible. Zero-knowledge proof algorithms may generally include a set of two algorithms, a prover algorithm, or “P,” which is used to prove computational integrity and/or possession of a secret, and a verifier algorithm, or “V” whereby a party may check the validity of P. Zero-knowledge proof may include an interactive zero-knowledge proof, wherein a party verifying the proof must directly interact with the proving party; for instance, the verifying and proving parties may be required to be online, or connected to the same network as each other, at the same time. Interactive zero-knowledge proof may include a “proof of knowledge” proof, such as a Schnorr algorithm for proof on knowledge of a discrete logarithm. in a Schnorr algorithm, a prover commits to a randomness r, generates a message based on r, and generates a message adding r to a challenge c multiplied by a discrete logarithm that the prover is able to calculate; verification is performed by the verifier who produced c by exponentiation, thus checking the validity of the discrete logarithm. Interactive zero-knowledge proofs may alternatively or additionally include sigma protocols. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various alternative interactive zero-knowledge proofs that may be implemented consistently with this disclosure.

Alternatively, zero-knowledge proof may include a non-interactive zero-knowledge, proof, or a proof wherein neither party to the proof interacts with the other party to the proof; for instance, each of a party receiving the proof and a party providing the proof may receive a reference datum which the party providing the proof may modify or otherwise use to perform the proof. As a non-limiting example, zero-knowledge proof may include a succinct non-interactive arguments of knowledge (ZK-SNARKS) proof, wherein a “trusted setup” process creates proof and verification keys using secret (and subsequently discarded) information encoded using a public key cryptographic system, a prover runs a proving algorithm using the proving key and secret information available to the prover, and a verifier checks the proof using the verification key; public key cryptographic system may include RSA, elliptic curve cryptography, ElGamal, or any other suitable public key cryptographic system. Generation of trusted setup may be performed using a secure multiparty computation so that no one party has control of the totality of the secret information used in the trusted setup; as a result, if any one party generating the trusted setup is trustworthy, the secret information may be unrecoverable by malicious parties. As another non-limiting example, non-interactive zero-knowledge proof may include a Succinct Transparent Arguments of Knowledge (ZK-STARKS) zero-knowledge proof. In an embodiment, a ZK-STARKS proof includes a Merkle root of a Merkle tree representing evaluation of a secret computation at some number of points, which may be 1 billion points, plus Merkle branches representing evaluations at a set of randomly selected points of the number of points; verification may include determining that Merkle branches provided match the Merkle root, and that point verifications at those branches represent valid values, where validity is shown by demonstrating that all values belong to the same polynomial created by transforming the secret computation. In an embodiment, ZK-STARKS does not require a trusted setup.

Zero-knowledge proof may include any other suitable zero-knowledge proof. Zero-knowledge proof may include, without limitation bulletproofs. Zero-knowledge proof may include a homomorphic public-key cryptography (hPKC)-based proof. Zero-knowledge proof may include a discrete logarithmic problem (DLP) proof. Zero-knowledge proof may include a secure multi-party computation (MPC) proof. Zero-knowledge proof may include, without limitation, an incrementally verifiable computation (IVC). Zero-knowledge proof may include an interactive oracle proof (IOP). Zero-knowledge proof may include a proof based on the probabilistically checkable proof (PCP) theorem, including a linear PCP (LPCP) proof. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various forms of zero-knowledge proofs that may be used, singly or in combination, consistently with this disclosure.

In an embodiment, secure proof is implemented using a challenge-response protocol. In an embodiment, this may function as a one-time pad implementation; for instance, a manufacturer or other trusted party may record a series of outputs (“responses”) produced by a device possessing secret information, given a series of corresponding inputs (“challenges”), and store them securely. In an embodiment, a challenge-response protocol may be combined with key generation. A single key may be used in one or more digital signatures as described in further detail below, such as signatures used to receive and/or transfer possession of crypto-currency assets; the key may be discarded for future use after a set period of time. In an embodiment, varied inputs include variations in local physical parameters, such as fluctuations in local electromagnetic fields, radiation, temperature, and the like, such that an almost limitless variety of private keys may be so generated. Secure proof may include encryption of a challenge to produce the response, indicating possession of a secret key. Encryption may be performed using a private key of a public key cryptographic system, or using a private key of a symmetric cryptographic system; for instance, trusted party may verify response by decrypting an encryption of challenge or of another datum using either a symmetric or public-key cryptographic system, verifying that a stored key matches the key used for encryption as a function of at least a device-specific secret. Keys may be generated by random variation in selection of prime numbers, for instance for the purposes of a cryptographic system such as RSA that relies prime factoring difficulty. Keys may be generated by randomized selection of parameters for a seed in a cryptographic system, such as elliptic curve cryptography, which is generated from a seed. Keys may be used to generate exponents for a cryptographic system such as Diffie-Helman or ElGamal that are based on the discrete logarithm problem.

Embodiments described in this disclosure may utilize, evaluate, and/or generate digital signatures. A “digital signature,” as used herein, includes a secure proof of possession of a secret by a signing device, as performed on provided element of data, known as a “message.” A message may include an encrypted mathematical representation of a file or other set of data using the private key of a public key cryptographic system. Secure proof may include any form of secure proof as described above, including without limitation encryption using a private key of a public key cryptographic system as described above. Signature may be verified using a verification datum suitable for verification of a secure proof; for instance, where secure proof is enacted by encrypting message using a private key of a public key cryptographic system, verification may include decrypting the encrypted message using the corresponding public key and comparing the decrypted representation to a purported match that was not encrypted; if the signature protocol is well-designed and implemented correctly, this means the ability to create the digital signature is equivalent to possession of the private decryption key and/or device-specific secret. Likewise, if a message making up a mathematical representation of file is well-designed and implemented correctly, any alteration of the file may result in a mismatch with the digital signature; the mathematical representation may be produced using an alteration-sensitive, reliably reproducible algorithm, such as a hashing algorithm as described above. A mathematical representation to which the signature may be compared may be included with signature, for verification purposes; in other embodiments, the algorithm used to produce the mathematical representation may be publicly available, permitting the easy reproduction of the mathematical representation corresponding to any file.

In some embodiments, digital signatures may be combined with or incorporated in digital certificates. In one embodiment, a digital certificate is a file that conveys information and links the conveyed information to a “certificate authority” that is the issuer of a public key in a public key cryptographic system. Certificate authority in some embodiments contains data conveying the certificate authority's authorization for the recipient to perform a task. The authorization may be the authorization to access a given datum. The authorization may be the authorization to access a given process. In some embodiments, the certificate may identify the certificate authority. The digital certificate may include a digital signature.

In some embodiments, a third party such as a certificate authority (CA) is available to verify that the possessor of the private key is a particular entity; thus, if the certificate authority may be trusted, and the private key has not been stolen, the ability of an entity to produce a digital signature confirms the identity of the entity and links the file to the entity in a verifiable way. Digital signature may be incorporated in a digital certificate, which is a document authenticating the entity possessing the private key by authority of the issuing certificate authority and signed with a digital signature created with that private key and a mathematical representation of the remainder of the certificate. In other embodiments, digital signature is verified by comparing the digital signature to one known to have been created by the entity that purportedly signed the digital signature; for instance, if the public key that decrypts the known signature also decrypts the digital signature, the digital signature may be considered verified. Digital signature may also be used to verify that the file has not been altered since the formation of the digital signature.

Referring now to FIG. 1A, an exemplary embodiment of a system for authentication of an electric aircraft for recharging (or charging) is illustrated. System 100 includes a computing device 104. Computing device 104 may include any computing device as described in this disclosure, including without limitation a microcontroller, microprocessor, digital signal processor (DSP) and/or system on a chip (SoC) as described in this disclosure. Computing device may include, be included in, and/or communicate with a mobile device such as a mobile telephone or smartphone. Computing device 104 may include a single computing device operating independently, or may include two or more computing device operating in concert, in parallel, sequentially or the like; two or more computing devices may be included together in a single computing device or in two or more computing devices. Computing device 104 may interface or communicate with one or more additional devices as described below in further detail via a network interface device. Network interface device may be utilized for connecting computing device 104 to one or more of a variety of networks, and one or more devices. Examples of a network interface device include, but are not limited to, a network interface card (e.g., a mobile network interface card, a LAN card), a modem, and any combination thereof. Examples of a network include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a data network associated with a telephone/voice provider (e.g., a mobile communications provider data and/or voice network), a direct connection between two computing devices, and any combinations thereof. A network may employ a wired and/or a wireless mode of communication. In general, any network topology may be used. Information (e.g., data, software etc.) may be communicated to and/or from a computer and/or a computing device. Computing device 104 may include but is not limited to, for example, a computing device or cluster of computing devices in a first location and a second computing device or cluster of computing devices in a second location.

Computing device 104 may include one or more computing devices dedicated to data storage, security, distribution of traffic for load balancing, and the like. Computing device 104 may distribute one or more computing tasks as described below across a plurality of computing devices of computing device, which may operate in parallel, in series, redundantly, or in any other manner used for distribution of tasks or memory between computing devices. Computing device 104 may be implemented using a “shared nothing” architecture in which data is cached at the worker, in an embodiment, this may enable scalability of system 100 and/or computing device.

With continued reference to FIG. 1A, computing device 104 may be designed and/or configured to perform any method, method step, or sequence of method steps in any embodiment described in this disclosure, in any order and with any degree of repetition. For instance, computing device 104 may be configured to perform a single step or sequence repeatedly until a desired or commanded outcome is achieved; repetition of a step or a sequence of steps may be performed iteratively and/or recursively using outputs of previous repetitions as inputs to subsequent repetitions, aggregating inputs and/or outputs of repetitions to produce an aggregate result, reduction or decrement of one or more variables such as global variables, and/or division of a larger processing task into a set of iteratively addressed smaller processing tasks. Computing device 104 may perform any step or sequence of steps as described in this disclosure in parallel, such as simultaneously and/or substantially simultaneously performing a step two or more times using two or more parallel threads, processor cores, or the like; division of tasks between parallel threads and/or processes may be performed according to any protocol suitable for division of tasks between iterations. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various ways in which steps, sequences of steps, processing tasks, and/or data may be subdivided, shared, or otherwise dealt with using iteration, recursion, and/or parallel processing.

Still referring to FIG. 1A, in some embodiments, system 100 includes a connector or charging connector 108 configured to authenticate an electric aircraft for recharging (or charging). In modified embodiments, system 100 may include a recharging (or charging) structure or station which may include charging connector 108. System 100 may be used in support of an electric aircraft. For instance, system 100 may be used to charge and/or recharge an electric aircraft. In some cases, system 100 may be tethered to electric aircraft during support. In some cases, system 100 may be tethered to a physical location on ground, for example an electrical power supply or source. Alternatively, system 100 may not be tethered to a physical location on the ground and may be substantially free to move when not tethered to an electric vehicle. System 100 may be configured to charge and/or recharge an electric aircraft. As used in this disclosure, “charging” or “recharging” refers to a process of increasing energy stored within an energy source. In some cases, an energy source may include at least a battery and charging may include providing an electrical flow or current to at least a battery. As used in this disclosure, an “electrical flow” or “current” is a flow of charged particles (e.g. electrons) or an electric current flowing within a material or structure which is capable of conducting it. Current may be measured in amperes or the like. As used in this disclosure, a “battery pack” is a set of any number of identical (or non-identical) batteries or individual battery cells. These may be configured in a series, parallel or a mixture of both configuration to deliver a desired electrical flow, current, voltage, capacity, or power density, as needed or desired. A battery may include, without limitation, one or more cells, in which chemical energy is converted into electricity (or electrical energy) and used as a source of energy or power.

Still referring to FIG. 1A, in some embodiments, system 100 may be used to authenticate and/or verify an identity associated with an electric aircraft to enable (or disable) recharging (or charging) of the electric aircraft. Charging connector 108 in conjunction with computing device 104 may be used to authenticate electric aircraft. In an embodiment, charging connector 108 may include computing device 104. Stated differently, computing device 104 may be part of charging connector 108. In another embodiment, computing device 104 may be separate from charging connector 108 and may be remote or spaced from the charging connector 108. In yet another embodiment, part of computing device 104 may be included in charging connector 108 and another part of the computing device 104 may be separate from the charging connector 108.

Still referring to FIG. 1A, in some embodiments, system 100 for authentication of an electric aircraft for recharging (or charging) includes charging connector 108 and computing device 104. Charging connector 108 is configured to receive an authentication datum 144 from an electric aircraft 136 and to mate with an electric aircraft port 132 of electric aircraft 136. Computing device 104 is communicatively connected to charging connector 108. Computing device 104 is configured to verify authentication datum 144, and enable, at charging connector 108, charging (or recharging) of electric aircraft 136 as a function of verification of authentication datum 144.

Continuing to refer to FIG. 1A, as used in this disclosure, “communicatively connected” means connected by way of a connection, attachment or linkage between two or more relata which allows for reception and/or transmittance of information therebetween. For example, and without limitation, this connection may be wired or wireless, direct or indirect, and between two or more components, circuits, devices, systems, and the like, which allows for reception and/or transmittance of data and/or signal(s) therebetween. Data and/or signals therebetween may include, without limitation, electrical, electromagnetic, magnetic, video, audio, radio and microwave data and/or signals, combinations thereof, and the like, among others. A communicative connection may be achieved, for example and without limitation, through wired or wireless electronic, digital or analog, communication, either directly or by way of one or more intervening devices or components. Further, communicative connection may include electrically coupling or connecting at least an output of one device, component, or circuit to at least an input of another device, component, or circuit. For example, and without limitation, via a bus or other facility for intercommunication between elements of a computing device. Communicative connecting may also include indirect connections via, for example and without limitation, wireless connection, radio communication, low power wide area network, optical communication, magnetic, capacitive, or optical coupling, and the like. In some instances, the terminology “communicatively coupled” may be used in place of communicatively connected in this disclosure.

With continued reference to FIG. 1A, in some embodiments, charging connector 108 may include a housing 112, at least a current conductor 116, at least a ground conductor 128 and at least a control pilot 120. Housing 112 may be configured to mate with electric aircraft port 132 of electric aircraft 136. At least a current conductor 116 may be configured to conduct a current. At least a ground conductor 128 may be configured to conduct to ground. At least a control pilot 120 may be configured to conduct a control signal. Each of at least a current conductor 116, at least a ground conductor 128 and at least a control pilot 120 may be configured to make a connection with a mating component on electric aircraft port 132 when housing 112 is mated with electric aircraft port 132. Control pilot(s) may be communicatively connected to computing device 104. Control pilot(s) 120 may be included in computing device 104 or it may be separate from computing device 104.

Still referring to FIG. 1A, current conductor(s) 116 and control pilot(s) 120 may be included and/or incorporated in a single element, unit or conductor which conducts both current and signals. Control pilot may also be interchangeably referred to as control signal conductor in the present disclosure. Electric aircraft 136 may include an of the aircrafts as disclosed herein. In an embodiment, electric aircraft 136 may include an electric vertical takeoff and landing (eVTOL) aircraft. In another embodiment, electric aircraft 136 may include a hybrid-electric aircraft. FIG. 2 also illustrates an electric aircraft in accordance with some exemplary embodiments.

Still referring to FIG. 1A, charging connector 108 may be configured in various manners, as needed or desired, for example and without limitation, to facilitate charging or recharging of electric aircraft 136. As used in this disclosure, a “connector” is a distal end of a tether or a bundle of tethers, e.g., hose, tubing, cables, wires, and the like, which is configured to removably attach with a mating component, for example without limitation a port. As used in this disclosure, a “port” is an interface for example of an interface configured to receive another component or an interface configured to transmit and/or receive signal on a computing device. For example in the case of an electric vehicle port, the port may interface with a number of conductors and/or a coolant flow path by way of receiving a connector. In the case of a computing device port, the port may provide an interface between a signal and a computing device. A connector may include a male component having a penetrative form and port may include a female component having a receptive form, receptive to the male component. Alternatively or additionally, connector may have a female component and port may have a male component. In some cases, connector may include multiple connections, which may make contact and/or communicate with associated mating components within port, when the connector is mated with the port.

With continued reference to FIG. 1A, certain features of systems, methods and connectors including a charging connector, controller, sensors and associated components and devices, which may efficaciously be utilized in accordance with certain embodiments of the present disclosure are disclosed in U.S. Nonprovisional application Ser. No. 17/405,840, filed on Aug. 18, 2021, entitled “CONNECTOR AND METHODS OF USE FOR CHARGING AN ELECTRIC VEHICLE,” U.S. Nonprovisional application Ser. No. 17/515,512, filed on Oct. 31, 2021, entitled “PROXIMITY DETECTION SYSTEMS AND METHODS FOR FACILITATING CHARGING OF ELECTRIC AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/515,508, filed on Oct. 31, 2021, entitled “CONNECTOR WITH AMBIENCE MONITORING CAPABILITY AND METHODS OF USE FOR CHARGING AN ELECTRIC AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/515,515, filed on Oct. 31, 2021, entitled “CONNECTOR WITH OVERVOLTAGE PROTECTION AND METHODS OF USE FOR CHARGING AN ELECTRIC AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/515,594, filed on Nov. 1, 2021, entitled “SYSTEMS AND METHODS FOR PRE-CHARGING SHORT CIRCUIT DETECTION IN ELECTRIC AIRCRAFT,” and U.S. Nonprovisional application Ser. No. 17/515,521, filed on Oct. 31, 2021, entitled “SYSTEMS AND METHODS FOR REGULATING CHARGING OF AN ELECTRIC AIRCRAFT,” the entirety of each one of which is incorporated herein by reference.

Still referring to FIG. 1A, charging connector 108 may include multiple interfaces required for fast charging of electric vehicles including electric aircrafts. In an embodiment, connector 108 may include a coolant flow path, or a distal end thereof, configured to contain a flow of a coolant. For example, and without limitation, connector 108 may include a coolant interface to deliver coolant to at least a battery 152 of electric vehicle or aircraft 136 during charging or recharging. Connector 108 may include cooling of power contacts and/or cables within connector to prevent overheating of those elements during recharging as well. Coolant flow path may be in fluidic communication with a coolant source. As used in this disclosure, a “coolant source” is an origin, generator, reservoir, or flow producer of coolant. In some cases, coolant source may include a flow producer, such as a fan and/or a pump. Coolant source may include any of following non-limiting examples, air conditioner, refrigerator, heat exchanger, pump, fan, expansion valve, and the like.

Still referring to FIG. 1A, as used in this disclosure, “coolant” is any flowable heat transfer medium. Coolant may include a liquid, a gas, a solid, and/or a fluid. Coolant may include a compressible fluid and/or a non-compressible fluid. Coolant may include a non-electrically conductive liquid such as a fluorocarbon-based fluid, such as without limitation Fluorinert™ from 3M of Saint Paul, Minn., USA. In some cases, coolant may include air. As used in this disclosure, a “flow of coolant” is a stream of coolant. In some cases, coolant may include a fluid and coolant flow is a fluid flow. Alternatively or additionally, in some cases, coolant may include a solid (e.g., bulk material) and coolant flow may include motion of the solid. Exemplary forms of mechanical motion for bulk materials include fluidized flow, augers, conveyors, slumping, sliding, rolling, and the like. Connectors and associated features of certain cooling embodiments are disclosed in U.S. Nonprovisional application Ser. No. 17/405,840, filed on Aug. 18, 2021, entitled “CONNECTOR AND METHODS OF USE FOR CHARGING AN ELECTRIC VEHICLE,”.

Continuing to refer to FIG. 1A, housing 112 of connector 108 may include, house or contain various components, as needed or desired. As used in this disclosure, a “housing” is a physical component within which other internal components are located. In some cases, internal components with housing will be functional while function of housing may largely be to protect the internal components. Housing and/or connector may be configured to mate with a port, for example electrical aircraft port 132. As used in this disclosure, “mate” is an action of attaching two or more components together. As used in this disclosure, an “electric aircraft port” is a port located on electric aircraft 136. Mating may be performed using a mechanical or electromechanical means described in this disclosure. For example, without limitation mating may include an electromechanical device used to join electrical conductors and create an electrical circuit. In some cases, mating may be performed by way of gendered mating components. A gendered mate may include a male component or plug which is inserted within a female component or socket. In some cases, mating may be removable. In some cases, mating may be permanent. In some cases, mating may be removable, but require a specialized tool or key for removal. Mating may be achieved by way of one or more of plug and socket mates, pogo pin contact, crown spring mates, and the like. In some cases, mating may be keyed to ensure proper alignment of connector 108. In some cases, mate may be lockable. As used in this disclosure, a “mating component” is a component that is configured to mate with at least another component, for example in a certain (i.e., mated) configuration. As used in this disclosure, an “electric vehicle” is any electrically powered means of human transport, for example without limitation an electric aircraft or electric vertical take-off and landing (eVTOL) aircraft. In some cases, an electric vehicle or aircraft may include an energy source configured to power at least a motor configured to move the electric vehicle or aircraft. As used in this disclosure, an “electric aircraft” is an electrically powered aircraft such as one powered by one or more electric motors or the like. In some embodiments, electric (or electrically powered) aircraft may be an electric vertical takeoff and landing (eVTOL) aircraft. As also noted above, FIG. 2 illustrates an electric aircraft in accordance with some exemplary embodiments.

Still referring to FIG. 1A, housing 112 may efficaciously be fabricated from various suitable materials, as needed or desired. In some embodiments, housing 112 may be fabricated from an electrically non-conducting material which may desirably be lightweight and have sufficient structural strength. In some cases, and without limitation, housing 112 may include a plastic or a thermoplastic material. For example, and without limitation, housing 212 may include an elastomer, a polyurethane, a thermoplastic polyurethane (TPU), a polycarbonate, a polycarbonate blend and/or a polycarbonate resin, combinations thereof, and the like, among others. Other suitable materials for housing may include ceramics, and the like.

With continued reference to FIG. 1A, connector (or charging connector) 108 and/or housing 112 of connector may include a fastener. As used in this disclosure, a “fastener” is a physical component that is designed and/or configured to attach or fasten two (or more) components together. Connector may include one or more attachment components or mechanisms, for example without limitation fasteners, threads, snaps, canted coil springs, and the like. In some cases, connector may be connected to port by way of one or more press fasteners. As used in this disclosure, a “press fastener” is a fastener that couples a first surface to a second surface when the two surfaces are pressed together. Some press fasteners include elements on the first surface that interlock with elements on the second surface; such fasteners include without limitation hook-and-loop fasteners such as VELCRO fasteners produced by Velcro Industries B.V. Limited Liability Company of Curacao Netherlands, and fasteners held together by a plurality of flanged or “mushroom”-shaped elements, such as 3M DUAL LOCK fasteners manufactured by 3M Company of Saint Paul, Minn. Press-fastener may also include adhesives, including reusable gel adhesives, GECKSKIN adhesives developed by the University of Massachusetts in Amherst, of Amherst, Mass., or other reusable adhesives. Where press-fastener includes an adhesive, the adhesive may be entirely located on the first surface of the press-fastener or on the second surface of the press-fastener, allowing any surface that can adhere to the adhesive to serve as the corresponding surface. In some cases, connector may be connected to port by way of magnetic force. For example, connector may include one or more of a magnetic, a ferro-magnetic material, and/or an electromagnet. Fastener may be configured to provide removable attachment between charging connector 108 and at least a port, for example, electric aircraft port 132. As used in this disclosure, “removable attachment” is an attributive term that refers to an attribute of one or more relata to be attached to and subsequently detached from another relata; removable attachment is a relation that is contrary to permanent attachment wherein two or more relata may be attached without any means for future detachment. Exemplary non-limiting methods of permanent attachment include certain uses of adhesives, glues, nails, engineering interference (i.e., press) fits, and the like. In some cases, detachment of two or more relata permanently attached may result in breakage of one or more of the two or more relata.

Still referring to FIG. 1A, connector (or charging connector) 108 and/or current conductor(s) 116 may be configured to charge or recharge electric aircraft 136 and/or battery(ies) 152 by conducting, transmitting or providing an electrical flow, charging current 168 and/or a charging voltage 148. In an embodiment, current conductor 116 may include an alternating current (AC) conductor configured to conduct an alternating current (AC). In an embodiment, current conductor 116 may include a direct current (DC) conductor configured to conduct a direct current (DC). In some embodiments, current conductor(s) 116 may include an AC pin and/or a DC pin.

Still referring to FIG. 1A, as used in this disclosure, a “conductor” is a component that facilitates conduction. As used in this disclosure, “conduction” is a process by which one or more of heat and/or electricity is transmitted through a substance, for example when there is a difference of effort (i.e., temperature or electrical potential) between adjoining regions. As also noted above, a “current” is a flow of charged particles (e.g. electrons) or an electric current flowing within a material or structure which is capable of conducting it. Current may be measured in amperes or the like. As used in this disclosure, a “current conductor” is a conductor capable of conducting an electric current. In some cases, and without limitation, current conductor(s) 116 may be configured to charge and/or recharge an electric vehicle such as, without limitation, electric aircraft 136. For instance, current conductor 116 may be connected to a power (or energy) supply (or source) 140 and current conductor may be designed and/or configured to facilitate a specified amount of electrical power, current, or current type. For example, current conductor 116 may include a direct current (DC) conductor. As used in this disclosure, a “direct current conductor” is a conductor configured to carry a direct current for charging or recharging an energy source (e.g. battery of electric aircraft). As used in this disclosure, “direct current” is one-directional flow of electric charge. In some cases, current conductor 116 may include an alternating current (AC) conductor. As used in this disclosure, an “alternating current conductor” is a conductor configured to carry an alternating current for charging or recharging an energy source (e.g. battery of electric aircraft). As used in this disclosure, an “alternating current” is a flow of electric charge that periodically reverses direction; in some cases, and without limitation, an alternating current may change its magnitude continuously with time (e.g., sine wave).

Continuing to refer to FIG. 1A, in an embodiment, system 100 and/or connector 108 may include an alternating current (AC) to direct current (DC) converter configured to convert an alternating current from power supply 140 to a direct current. As used in this disclosure, an “alternating current to direct current converter” is an electrical component that is configured to convert alternating current to direct current. An alternating current to direct current (AC-DC) converter may include an alternating current to direct current power supply and/or transformer. In some cases, AC-DC converter may be located within an electric vehicle or aircraft and conductors may provide an alternating current to the electric vehicle by way of connector 108. Alternatively and/or additionally, in some cases, AC-DC converter may be located outside of electric vehicle or aircraft and an electrical charging current may be provided by way of a direct current to electric vehicle or aircraft.

With continued reference to FIG. 1A, in some embodiments, current conductor 116 may be in electric communication with (and/or be communicatively connected to) a power supply 140. Conductor may be a physical device and/or object that facilitates conduction, for example electrical conduction and/or thermal conduction. In some cases, conductor may be an electrical conductor, for example a wire and/or cable. Exemplary conductor materials include metals, such as without limitation copper, nickel, steel, and the like. As used in this disclosure, “communication” is an attribute wherein two or more relata interact with one another, for example within a specific domain or in a certain manner. In some cases communication between two or more relata may be of a specific domain, such as without limitation electric communication, fluidic communication, informatic communication, mechanic communication, and the like. As used in this disclosure, “electric communication” is an attribute wherein two or more relata interact with one another by way of an electric current or electricity in general. As used in this disclosure, “fluidic communication” is an attribute wherein two or more relata interact with one another by way of a fluidic flow or fluid in general. As used in this disclosure, “informatic communication” is an attribute wherein two or more relata interact with one another by way of an information flow or information in general. As used in this disclosure, “mechanic communication” is an attribute wherein two or more relata interact with one another by way of mechanical means, for instance mechanic effort (e.g., force) and flow (e.g., velocity).

Still referring to FIG. 1A, in some embodiments, connector 108 may include ground conductor(s) 128. As used in this disclosure, a “ground conductor” is a conductor configured to be in electrical communication with a ground. As used in this disclosure, a “ground” is a reference point in an electrical circuit, a common return path for electric current, or a direct physical connection to the earth. Ground may include an absolute ground such as earth or ground may include a relative (or reference) ground, for example in a floating configuration. Ground conductor 128 functions to provide a grounding or earthing path, for example, for any abnormal, excess or stray electricity or electrical flow.

With continued reference to FIG. 1A, connector 108 may include a proximity signal conductor or proximity pilot. As used in this disclosure, an “proximity signal conductor” is a conductor configured to carry a proximity signal. As used in this disclosure, a “proximity signal” is a signal that is indicative of information about a location of connector. Proximity signal may be indicative of attachment of connector with a port, for instance an electric vehicle port and/or a test port. In some cases, a proximity signal may include an analog signal, a digital signal, an electrical signal, an optical signal, a fluidic signal, or the like. In some cases, a proximity signal conductor may be configured to conduct a proximity signal indicative of attachment between connector 108 and a port, for example electric aircraft port 132.

Still referring to FIG. 1A, in some cases, system 100 and/or connector 108 may additionally include a proximity sensor. Proximity sensor may be electrically communicative with a proximity signal conductor. Proximity sensor may be configured to generate a proximity signal as a function of connection between connector 108 and a port, for example electric vehicle port 112. As used in this disclosure, a “proximity sensor” is a sensor that is configured to detect at least a phenomenon related to connecter being mated to a port. Proximity sensor may include any sensor described in this disclosure, including without limitation a switch, a capacitive sensor, a capacitive displacement sensor, a doppler effect sensor, an inductive sensor, a magnetic sensor, an optical sensor (such as without limitation a photoelectric sensor, a photocell, a laser rangefinder, a passive charge-coupled device, a passive thermal infrared sensor, and the like), a radar sensor, a reflection sensor, a sonar sensor, an ultrasonic sensor, fiber optics sensor, a Hall effect sensor, and the like. Certain features of proximity signal conductors, proximity sensor and/or associated components and devices, which may efficaciously be utilized in accordance with certain embodiments of the present disclosure are disclosed in U.S. Nonprovisional application Ser. No. 17/405,840, filed on Aug. 18, 2021, entitled “CONNECTOR AND METHODS OF USE FOR CHARGING AN ELECTRIC VEHICLE,”.

With continued reference to FIG. 1A, in some embodiments, control pilot 120 may be configured to conduct control signal(s). As used in this disclosure, a “control pilot” or “control signal conductor” is a conductor configured to carry a control signal between an electric vehicle (e.g. electric aircraft 136) and a charger (e.g. connector 108) which also has control circuitry to enable determinations based on a received signal. As used in this disclosure, a “control signal” is an electrical signal that is indicative of information. As also noted above, in this disclosure, control pilot may be used interchangeably with control signal conductor. In some cases, and without limitation, control signal may include an analog signal or a digital signal. In some embodiments, control signal may be communicated from one or more aircraft sensor(s) 160, including sensors configured to detect characteristics of battery 152 and/or energy source 156, and/or one or more connector sensor(s) 164. This control signal may then be provided to one or more controllers (or computing devices) such as computing devices 104 and/or a controller of aircraft 136 (e.g. flight controller 124). In some embodiments, control signal may include an authentication signal or authentication datum 144 of electric aircraft which may be transmitted or provided to computing device 104 and/or control pilot 120.

Still referring to FIG. 1A, in some cases, control signal may be communicated from one or more sensors, for example located within electric vehicle or aircraft 136. For example, in some cases, control signal may be associated with a battery within an electric vehicle or aircraft 136. For example, control signal may include a battery sensor signal. As used in this disclosure, a “battery sensor signal” is a signal representative of a characteristic of a battery. In some cases, battery sensor signal may be representative of a characteristic of an electric vehicle or aircraft battery (e.g. battery 152), for example, during a pre-charging stage or phase and/or as electric vehicle or aircraft battery is being charged or recharged. In some versions, computing device 104 may additionally include a sensor interface configured to receive a sensor signal. Sensor interface may include one or more ports, an analog to digital converter, and the like. In some cases, a sensor, a circuit, and/or a computing device 104 may perform one or more signal processing steps on a signal. For instance, sensor, circuit or computing device 104 may analyze, modify, and/or synthesize a signal in order to improve the signal, for instance by improving transmission, storage efficiency, or signal to noise ratio. In some embodiments, control signal may include authentication datum 144.

With continued reference to FIG. 1A, exemplary methods of signal processing may include analog, continuous time, discrete, digital, nonlinear, and statistical. Analog signal processing may be performed on non-digitized or analog signals. Exemplary analog processes may include passive filters, active filters, additive mixers, integrators, delay lines, compandors, multipliers, voltage-controlled filters, voltage-controlled oscillators, and phase-locked loops. Continuous-time signal processing may be used, in some cases, to process signals which varying continuously within a domain, for instance time. Exemplary non-limiting continuous time processes may include time domain processing, frequency domain processing (Fourier transform), and complex frequency domain processing. Discrete time signal processing may be used when a signal is sampled non-continuously or at discrete time intervals (i.e., quantized in time). Analog discrete-time signal processing may process a signal using the following exemplary circuits sample and hold circuits, analog time-division multiplexers, analog delay lines and analog feedback shift registers. Digital signal processing may be used to process digitized discrete-time sampled signals. Commonly, digital signal processing may be performed by a computing device or other specialized digital circuits, such as without limitation an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a specialized digital signal processor (DSP). Digital signal processing may be used to perform any combination of typical arithmetical operations, including fixed-point and floating-point, real-valued and complex-valued, multiplication and addition. Digital signal processing may additionally operate circular buffers and lookup tables. Further non-limiting examples of algorithms that may be performed according to digital signal processing techniques include fast Fourier transform (FFT), finite impulse response (FIR) filter, infinite impulse response (IIR) filter, and adaptive filters such as the Wiener and Kalman filters. Statistical signal processing may be used to process a signal as a random function (i.e., a stochastic process), utilizing statistical properties. For instance, in some embodiments, a signal may be modeled with a probability distribution indicating noise, which then may be used to reduce noise in a processed signal.

Still referring to FIG. 1A, as used in this disclosure, a “sensor” is a device that is configured to detect a phenomenon and transmit information related to the detection of the phenomenon. For example, in some cases a sensor may transduce a detected phenomenon, such as without limitation, voltage, current, speed, direction, force, torque, temperature, pressure, and the like, into a sensed signal. Sensor may include one or more sensors which may be the same, similar or different. Sensor may include a plurality of sensors which may be the same, similar or different. Sensor may include one or more sensor suites with sensors in each sensor suite being the same, similar or different. Sensor may include, for example and without limitation, a current sensor, a voltage sensor, a resistance sensor, a Wheatstone bridge, a gyroscope, an accelerometer, a torque sensor, a magnetometer, an inertial measurement unit (IMU), a pressure sensor, a force sensor, a thermal sensor, a proximity sensor, a displacement sensor, a vibration sensor, a light sensor, an optical sensor, a pitot tube, a speed sensor, and the like, among others. Sensors in accordance with embodiments disclosed herein may be configured detect a plurality of data, such as and without limitation, data relating to battery state of charge (SOC), battery life cycle, battery consumption rate, battery temperature, and the like, among others.

With continued reference to FIG. 1A, any number of suitable sensors may be efficaciously used in conjunction with system 100. For example, and without limitation, these sensors may include current sensors, voltage sensors, multimeters, resistance sensors, impedance sensors, capacitance sensors, state of charge (SOC) sensors, battery health sensors, battery diagnostic sensors, Daly detectors, electroscopes, electron multipliers, Faraday cups, galvanometers, Hall effect sensors, Hall probes, magnetic sensors, optical sensors, magnetometers, magnetoresistance sensors, MEMS magnetic field sensors, metal detectors, planar Hall sensors, thermal sensors, and the like, among others. Aircraft (or battery) sensor(s) 160 and/or connector sensor(s) 164 may efficaciously include, without limitation, any of these sensors and any others as disclosed in the present disclosure.

Still referring to FIG. 1A, computing device 104 and/or connector 108 may be connected to power supply 140 which provides an electrical flow to connector 108. Computing device 104 may regulate, control and/or optimize a charging voltage 148 and/or charging current 168 that emanates from connector 108 to electric aircraft 136. This charging voltage 148 and/or charging current 168 may be used to charge or recharge energy source 156 and/or battery 152 of electric aircraft 136. As used in this disclosure, a “charging voltage” is an electrical flow at a predetermined voltage (and/or associated current) which may be constant or variable. As used in this disclosure, a “charging current” is an electrical flow at a predetermined current (and/or associated voltage) which may be constant or variable. This electrical flow of electrical charge facilitates an increase in stored electrical energy of an energy storage device, such as without limitation a battery. In some embodiments, charging voltage 148 and/or charging current 168 may be provided in a plurality of phases or stages to optimize charging of energy source 156 and/or battery 152. Each charging phase or stage may have a prescribed and/or optimized charging voltage and/or current which may be variable or constant. Any number of charging phases or stages may be utilized, as needed or desired, with each including a prescribed and/or optimized charging voltage and/or current. Energy source 156 may include, without limitation, one or more battery packs, battery modules, battery units, batteries, battery cells, cells, or the like, as needed or desired, which may efficaciously be located at different locations on aircraft 136.

With continued reference to FIG. 1A, as used in this disclosure, an “energy source” is a source (or supplier) of energy (or power) to power one or more components. For example, and without limitation, energy source may be configured provide energy to an aircraft power source that in turn that drives and/or controls any other aircraft component such as other flight components. An energy source may include, for example, an electrical energy source a generator, a photovoltaic device, a fuel cell such as a hydrogen fuel cell, direct methanol fuel cell, and/or solid oxide fuel cell, an electric energy storage device (e.g., a capacitor, an inductor, and/or a battery). An electrical energy source may also include a battery cell, a battery pack, or a plurality of battery cells connected in series into a module and each module connected in series or in parallel with other modules. Configuration of an energy source containing connected modules may be designed to meet an energy or power requirement and may be designed to fit within a designated footprint in an electric aircraft.

In an embodiment, and still referring to FIG. 1A, an energy source may be used to provide a steady supply of electrical flow or power to a load over the course of a flight by a vehicle or other electric aircraft. For example, an energy source may be capable of providing sufficient power for “cruising” and other relatively low-energy phases of flight. An energy source may also be capable of providing electrical power for some higher-power phases of flight as well, particularly when the energy source is at a high state of charge (SOC), as may be the case for instance during takeoff. In an embodiment, an energy source may be capable of providing sufficient electrical power for auxiliary loads including without limitation, lighting, navigation, communications, de-icing, steering or other systems requiring power or energy. Further, an energy source may be capable of providing sufficient power for controlled descent and landing protocols, including, without limitation, hovering descent or runway landing. As used herein an energy source may have high power density where electrical power an energy source can usefully produce per unit of volume and/or mass is relatively high. “Electrical power,” as used in this disclosure, is defined as a rate of electrical energy per unit time. An energy source may include a device for which power that may be produced per unit of volume and/or mass has been optimized, at the expense of the maximal total specific energy density or power capacity, during design. Non-limiting examples of items that may be used as at least an energy source may include batteries used for starting applications including Lithium ion (Li-ion) batteries which may include NCA, NMC, Lithium iron phosphate (LiFePO₄) and Lithium Manganese Oxide (LMO) batteries, which may be mixed with another cathode chemistry to provide more specific power if the application requires Li metal batteries, which have a lithium metal anode that provides high power on demand, Li ion batteries that have a silicon or titanite anode, energy source may be used, in an embodiment, to provide electrical power to an electric aircraft or drone, such as an electric aircraft vehicle, during moments requiring high rates of power output, including without limitation takeoff, landing, thermal de-icing and situations requiring greater power output for reasons of stability, such as high turbulence situations, as described in further detail below. A battery may include, without limitation a battery using nickel based chemistries such as nickel cadmium or nickel metal hydride, a battery using lithium ion battery chemistries such as a nickel cobalt aluminum (NCA), nickel manganese cobalt (NMC), lithium iron phosphate (LiFePO4), lithium cobalt oxide (LCO), and/or lithium manganese oxide (LMO), a battery using lithium polymer technology, lead-based batteries such as without limitation lead acid batteries, metal-air batteries, or any other suitable battery. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various devices of components that may be used as an energy source.

Still referring to FIG. 1A, an energy source may include a plurality of energy sources, referred to herein as a module of energy sources. A module may include batteries connected in parallel or in series or a plurality of modules connected either in series or in parallel designed to deliver both the power and energy requirements of the application. Connecting batteries in series may increase the voltage of at least an energy source which may provide more power on demand. High voltage batteries may require cell matching when high peak load is needed. As more cells are connected in strings, there may exist the possibility of one cell failing which may increase resistance in the module and reduce an overall power output as a voltage of the module may decrease as a result of that failing cell. Connecting batteries in parallel may increase total current capacity by decreasing total resistance, and it also may increase overall amp-hour capacity. Overall energy and power outputs of at least an energy source may be based on individual battery cell performance or an extrapolation based on measurement of at least an electrical parameter. In an embodiment where an energy source includes a plurality of battery cells, overall power output capacity may be dependent on electrical parameters of each individual cell. If one cell experiences high self-discharge during demand, power drawn from at least an energy source may be decreased to avoid damage to the weakest cell. An energy source may further include, without limitation, wiring, conduit, housing, cooling system and battery management system. Persons skilled in the art will be aware, after reviewing the entirety of this disclosure, of many different components of an energy source.

Continuing to refer to FIG. 1A, energy sources, battery packs, batteries, sensors, sensor suites and/or associated methods which may efficaciously be utilized in accordance with some embodiments are disclosed in U.S. Nonprovisional application Ser. No. 17/111,002, filed on Dec. 3, 2020, entitled “SYSTEMS AND METHODS FOR A BATTERY MANAGEMENT SYSTEM INTEGRATED IN A BATTERY PACK CONFIGURED FOR USE IN ELECTRIC AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/108,798, filed on Dec. 1, 2020, and entitled “SYSTEMS AND METHODS FOR A BATTERY MANAGEMENT SYSTEM INTEGRATED IN A BATTERY PACK CONFIGURED FOR USE IN ELECTRIC AIRCRAFT,” and U.S. Nonprovisional application Ser. No. 17/320,329, filed on May 14, 2021, and entitled “SYSTEMS AND METHODS FOR MONITORING HEALTH OF AN ELECTRIC VERTICAL TAKE-OFF AND LANDING VEHICLE,” the entirety of each one of which is incorporated herein by reference.

With continued reference to FIG. 1A, other energy sources, battery packs, batteries, sensors, sensor suites and/or associated methods which may efficaciously be utilized in accordance with some embodiments are disclosed in U.S. Nonprovisional application Ser. No. 16/590,496, filed on Oct. 2, 2019, and entitled “SYSTEMS AND METHODS FOR RESTRICTING POWER TO A LOAD TO PREVENT ENGAGING CIRCUIT PROTECTION DEVICE FOR AN AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/348,137, filed on Jun. 15, 2021, and entitled “SYSTEMS AND METHODS FOR RESTRICTING POWER TO A LOAD TO PREVENT ENGAGING CIRCUIT PROTECTION DEVICE FOR AN AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/008,721, filed on Sep. 1, 2020, and entitled “SYSTEM AND METHOD FOR SECURING BATTERY IN AIRCRAFT,” U.S. Nonprovisional application Ser. No. 16/948,157, filed on Sep. 4, 2020, and entitled “SYSTEM AND METHOD FOR HIGH ENERGY DENSITY BATTERY MODULE,” U.S. Nonprovisional application Ser. No. 16/948,140, filed on Sep. 4, 2020, and entitled “SYSTEM AND METHOD FOR HIGH ENERGY DENSITY BATTERY MODULE,” and U.S. Nonprovisional application Ser. No. 16/948,141, filed on Sep. 4, 2020, and entitled “COOLING ASSEMBLY FOR USE IN A BATTERY MODULE ASSEMBLY,” the entirety of each one of which is incorporated herein by reference. Still other energy sources, battery packs, batteries, sensors, sensor suites, charging connectors and/or associated methods which may efficaciously be utilized in accordance with some embodiments are disclosed in U.S. Nonprovisional application Ser. No. 17/405,840, filed on Aug. 18, 2021, entitled “CONNECTOR AND METHODS OF USE FOR CHARGING AN ELECTRIC VEHICLE,”.

Still referring to FIG. 1A, power supply 140 may be configured to provide an electrical flow or current to charging connector 108 and/or computing device 104. As used in this disclosure, a “power supply” is a source that supplies electrical power, for example for charging a battery. In some cases, power supply 140 may include a charging battery (i.e., a battery used for charging other batteries). A charging battery is notably contrasted with an electric vehicle or electric aircraft battery, which is located for example upon an electric aircraft. Charging battery of power supply 140 may include a plurality of batteries, battery modules, and/or battery cells. Charging battery of power supply may be configured to store a range of electrical energy, for example a range of between about 5 KWh and about 5,000 KWh. Power supply 140 may house a variety of electrical components. In one embodiment, power supply 140 may contain a solar inverter. Solar inverter may be configured to produce on-site power generation. In one embodiment, power generated from solar inverter may be stored in a charging battery. In some embodiments, charging battery of power supply may include a used electric vehicle battery no longer fit for service in a vehicle. Charging battery of power supply may include any battery described in this disclosure.

In some embodiments, and still referring to FIG. 1A, power supply 140 may have a continuous power rating of at least 350 kVA. In other embodiments, power supply 140 may have a continuous power rating of over 350 kVA. In some embodiments, power supply 140 may have a battery charge range up to 950 Vdc. In other embodiments, power supply 140 may have a battery charge range of over 950 Vdc. In some embodiments, power supply 140 may have a continuous charge current of at least 350 amps. In other embodiments, power supply 140 may have a continuous charge current of over 350 amps. In some embodiments, power supply 140 may have a boost charge current of at least 500 amps. In other embodiments, power supply 140 may have a boost charge current of over 500 amps. In some embodiments, power supply 140 may include any component with the capability of recharging an energy source of an electric vehicle or aircraft. In some embodiments, power supply 140 may include a constant voltage charger, a constant current charger, a taper current charger, a pulsed current charger, a negative pulse charger, an IUI charger, a trickle charger, and a float charger.

With continued reference to FIG. 1A, in some cases, power supply 140 may include one or more electrical components configured to control flow of an electric recharging current or switches, relays, direct current to direct current (DC-DC) converters, and the like. In some cases, power supply 140 may include one or more circuits configured to provide a variable current source to provide electric recharging current, for example an active current source. Non-limiting examples of active current sources include active current sources without negative feedback, such as current-stable nonlinear implementation circuits, following voltage implementation circuits, voltage compensation implementation circuits, and current compensation implementation circuits, and current sources with negative feedback, including simple transistor current sources, such as constant currant diodes, Zener diode current source circuits, LED current source circuits, transistor current, and the like, Op-amp current source circuits, voltage regulator circuits, and curpistor tubes, to name a few. In some cases, one or more circuits within power supply 140 or within communication with supply 140 may be configured to affect electrical recharging current according to control signal from controller 104, such that controller 104 may control at least a parameter of electrical charging current or voltage. For example, in some cases, controller 104 may control one or more of current (Amps), potential (Volts), and/or power (Watts) of electrical charging current or voltage by way of control signal. In some cases, controller 104 may be configured to selectively engage electrical charging current or voltage, for example ON or OFF by way of control signal.

Still referring to FIG. 1A, in some cases, an AC-DC converter may be used to recharge a charging battery of power supply 140. In some cases, AC-DC converter may be used to provide electrical power to power supply 140 and/or controller 104. In some embodiments, power supply 140 may have a connection to a grid power component. Grid power component may be connected to an external electrical power grid. In some embodiments, grid power component may be configured to slowly charge one or more batteries (e.g. of power supply 140) in order to reduce strain on nearby electrical power grids. In one embodiment, grid power component may have an AC grid current of at least 450 amps. In some embodiments, grid power component may have an AC grid current of more or less than 450 amps. In one embodiment, grid power component may have an AC voltage connection of 480 Vac. In other embodiments, grid power component may have an AC voltage connection of above or below 480 Vac. In some embodiments, power source 140 may provide power to the grid power component. In this configuration, power source 140 may provide power to a surrounding electrical power grid. Certain features including structure and electronic configuration of charging stations and power supplies (sources) which may efficaciously be used in conjunction with some embodiments of the present disclosure are disclosed in U.S. Nonprovisional application Ser. No. 17/405,840, filed on Aug. 18, 2021, entitled “CONNECTOR AND METHODS OF USE FOR CHARGING AN ELECTRIC VEHICLE,”.

Exemplary embodiments may be further understood without limitation, with reference to the table below.

Min. Max. Nom. Electrical charging  1 KW 200 KW 20 KW current power (AC) Electrical charging 10 Amps 450 Amps 80 Amps current (AC) Electrical charging  1 KW 250 KW 25 KW current power (DC) Electrical charging 10 Amps 500 Amps 50 Amps current (DC) Battery acceptable −30° C. +50° C. 0° C. temperature change during charging Conductor acceptable −30° C. +50° C. 0° C. temperature change during charging Coolant Air, water, water-glycol mix, anti-freeze, Fluorinert ™, ethylene glycol, propylene glycol, any combination thereof, and the like. Connector-Port mating Mated First: coolant flow source, proximity contact, isolation monitor sequence contacts. Mated Last: AC conductor, DC conductor, control signal. Conductor materials Copper, copper-alloys, noble metals, non-noble metals, carbon, diamond, graphite, platinum group metals, and the like. Conductor coatings Copper, copper-alloys, noble metals, non-noble metals, carbon, diamond, graphite, hard gold, hard gold flashed palladium-nickel (e.g., 80/20), tin, silver, diamond-like carbon, platinum-group metals, and the like.

Still referring to FIG. 1A, in some embodiments, and as also noted above, system 100 for authentication of an electric aircraft for recharging (or charging) includes charging connector 108 and computing device 104. Charging connector 108 is configured to receive authentication datum 144 from electric aircraft 136 and to mate with electric aircraft port 132 of electric aircraft 136. Computing device 104 is communicatively connected to charging connector 108. Computing device 104 is configured to verify authentication datum 144, and enable, at charging connector 108, charging (or recharging) of electric aircraft 136 as a function of verification of authentication datum 144. In some embodiments, an associated method for authentication of an electric aircraft for recharging is provided as also discussed in reference to at least FIG. 5 below. Method includes: receiving, at charging connector 108, authentication datum 144 from electric aircraft 136, wherein charging connector 108 is configured to mate with electric aircraft port 132 of electric aircraft 136; and verifying, at computing device 104 communicatively connected to charging connector 108, authentication datum 144; and enabling, by computing device 104, charging (or recharging) of electric aircraft 136, at charging connector 108, as a function of verification of authentication datum 144.

Still referring to FIG. 1A, charging (or recharging) connector 108 is configured to receive authentication datum 144 and may be located at a charging (or recharging) structure, station or the like. As used in this disclosure, a “charging structure” is a structure capable of supporting or facilitating charging or recharging of an electric vehicle. Electric vehicle may include, without limitation, an electric aircraft. Charging structure may include, without limitation, a larger scale structure such as a charging station or a smaller scale structure such as a charging connector (e.g. connector 108). Charging structure may also include other structures such as, without limitation, charging support equipment, computing devices, power supplies, sensors, transmitters, communication devices, and the like, among others.

Still referring to FIG. 1A, in an embodiment, charging structure may include a charging station. As used in this disclosure, a “charging station” is a site capable of accommodating an electric vehicle for charging or recharging. Electric vehicle may include, without limitation, an electric aircraft. Charging station may include, without limitation, a platform, a deck, a pad, a port, a strip, a surface, or the like capable of supporting an aircraft, wherein, whereon and/or whereat an electric aircraft may be charged or recharged. Thus, a charging station may be capable of providing electrical energy from a local or remote source and may be capable of allowing an aircraft to land thereat and takeoff therefrom. Charging station, for example and without limitation, may house or be coupled to other components and devices such as one or more computing devices, and the like, among others. Charging structure and/or charging station may include, for example and without limitation, any infrastructure, structure, site, station, port, location, facility, building, construct, arrangement, and the like, among others which may have a deck, pad, platform, strip, and the like, among others, suitable for facilitating the landing, takeoff and/or charging of an electric aircraft. Charging station may include a designated area for an eVTOL aircraft to land on and/or takeoff from. Charging station may be made from any suitable material and may be of any dimension, as needed or desired. Charging station may include, without limitation, a helideck, helipad and/or platform. In an embodiment, charging connector 108, charging structure and/or charging station may be configured to be detectable, for example, by electric aircraft. For example, and without limitation, charging connector's, charging structure's and/or charging station's location may be provided on a map or the like and/or it may have the capability to emit a signal detectable, for example, by electric aircraft. Charging structure may also to be referred to herein as “charging infrastructure” or “recharging infrastructure.” Charging structure and/or charging station may include, without limitation, one or more power sources or supplies, controllers, coolant sources or supplies, charging test ports, connectors, conductors, wires, cables, lines, and the like, among others.

Continuing to refer to FIG. 1A, charging connector 108 may receive authentication datum 144 from electric aircraft 136 by a number of suitable means. Connection between charging connector 108 and electric aircraft 136 for receiving authentication datum 144 may be a wireless (“unplugged”) or wired (“plugged”) connection that allows charging connector 108 and electric aircraft 136 to be communicatively connected. For example, and without limitation, a wired connection may use cables, wires, lines, and the like. In an embodiment, wired connection may be between electric aircraft port 132 and charging connector 108, for example, when charging connector 108 and/or its housing 112 are plugged into electric aircraft port 132. For instance, charging connector's control signal conductor (e.g. control pilot 120) may receive data from electric aircraft 136. A wireless connection may use electromagnetic signals, microwave signals, infrared signals, radio signals, mobile network signals, satellite signals, wi-fi signals, Bluetooth signals, and the like. In an embodiment, wireless connection may be between electric aircraft port 132 and charging connector 108. In some embodiments, authentication datum 144 may be provided to computing device 104. In some embodiments, receiving authentication datum 144 may further include communicatively connecting computing device 104 and electric aircraft 132. In some embodiments, authentication datum 144 may be provided by flight controller 124 to charging connector 108 and/or computing device 104. For a wireless connection, authentication datum 144 may be provided to charging connector 108 while aircraft is in-flight, taxing on runway, or generally still spaced from charging connector 108.

With continued reference to FIG. 1A, as used in this disclosure, an “authentication datum” is an element of information associated with an electric aircraft that may be used to authorize charging of the electric aircraft at a particular charging structure, station or connector; authentication datum may be used to verify or determine an identity of the electric aircraft or a user thereof. Authentication may considered to be a process or action of verifying an identity of a user or process. The same (or different) authentication may be used to authorize charging at a plurality or network of charging stations. Authentication may include, for example and without limitation, password-based authentication, multi-factor authentication, certificate-based authentication, biometric authentication, token-based authentication, and the like, among others.

Still referring to FIG. 1A, authentication datum 144 may include information, data or credentials on or relating to, for example, and without limitation, vehicle identification number (VIN) of electric aircraft, radio-frequency identification (RFID) associated with electric aircraft, registration and/or licensing of aircraft and/or pilot, identity of pilot of electric aircraft (e.g. credential, license or biometric based), identity of owner of electric aircraft, membership of pilot and/or aircraft in a fleet, airline, association, club, or the like, appointment time or reservation made for charging electric aircraft, and the like, among others. In some cases, authentication datum 144 may include a password or passcode which has to be entered, additionally or alternatively, to other authentication datum, data or information. Authentication datum 144 may also be transmitted to charging connector 108 by an independent device onboard or remote from electric aircraft, for example and without limitation, from a smartphone or tablet of a pilot or other operator. Authentication datum 144 may include a digital signature, for example, signed by a computing device on electric aircraft such as flight controller 124, or the like.

Still referring to FIG. 1A, in some embodiments, computing device 104 is configured to verify authentication datum 144. Verification may include referencing or checking one or more databases 172 which include data on electric aircrafts allowed access, in general or at a particular time, to charging connector 108, data on electric aircrafts compatible with charging connector 108, flagged electric aircrafts, and the like, among others. For example, hybrid-electric aircrafts and electric aircrafts with certain type and/or size of battery systems may not be compatible with a particular charging connector and/or its power supply. Alternatively, or additionally, verification may include connecting or interfacing with one or more networks 176, or the like. In an embodiment, verification may be performed using blockchain authentication. For example, charging connector 108 could serve as a public/private key. Blockchain authentication may be performed using cryptographic keys which may include a string of data that identifies a user and gives access to their “account” on a system. This can facilitate in creating a secure digital identity to authenticate the user via digital signatures and to ‘unlock’ the transaction they want to perform. Certain blockchain embodiments in accordance with the present disclosure are further discussed below with reference to FIG. 1B.

Continuing to refer to FIG. 1A, in some embodiments, computing device 104 is configured to enable, at charging connector 108, charging (or recharging) of electric aircraft 136 as a function of verification of authentication datum 144. If authentication datum 144 is verified, electric aircraft 136 would have permission to charge or recharge at charging connector 108. A control signal or the like may be provided to charging connector (and/or associated charging station) which would enable charging at that charging connector for that particular aircraft. If authentication datum 144 is not verified, electric aircraft 136 would be denied permission to charge or recharge at charging connector 108. A control signal or the like may be provided to charging connector (and/or associated charging station) which would disable charging at that charging connector for that particular aircraft.

With continued reference to FIG. 1A, suitable messages, notifications or alerts may be transmitted to electric aircraft 136 and/or other locations regarding authentication and/or verification associated with a particular aircraft and/or charging connector. For example, and without limitation, a message may be transmitted to electric aircraft notifying it that its charging request has been authorized—the message may include instructions on the charging process. In another example, and without limitation, a message may be transmitted to electric aircraft notifying it that its charging request has been denied—the message may include a request for further information and/or instructions on how to proceed further. In yet another example, a message may be transmitted to relevant authorities on a charging request received from an electric aircraft (and/or pilot) on a flagged list such as a red-flag list, no-fly list, watch list, or the like.

Still referring to FIG. 1A, in an embodiment, computing device 104 may be a part of charging connector 108. In an embodiment, charging connector 108 may be configured to communicatively connect to electric aircraft 136. In an embodiment, charging connector 108 further comprises control pilot 120, and wherein control pilot may be configured to electrically connect to electric aircraft port 132.

Continuing to refer to FIG. 1A, in an embodiment, authentication datum 144 may include information on an identification of electric aircraft 136. In an embodiment, authentication datum 144 may include information on an identification of an owner of electric aircraft 136. In an embodiment, authentication datum 144 may include information on a recharging appointment of electric aircraft 136. In an embodiment, authentication datum may include a passcode.

With continued reference to FIG. 1A, in an embodiment, computing device 104 may be further configured to verify authentication datum by accessing database 172. In an embodiment, computing device 104 may be further configured to enable charging of electric aircraft 136 by transmitting a control signal to charging connector 108.

Still referring to FIG. 1A, in some cases, charging connector 108 (and/or associated charging station) may be available to only authenticated aircraft. In other cases, charging connector 108 (and/or associated charging station) may be available to unauthenticated aircraft, for example and without limitation, in emergency situations. In still other cases, charging connector 108 (and/or associated charging station) may be utilized for planned charging (or recharging) of electric aircraft (e.g., when specified in flight plan) or unplanned charging (or recharging) of electric aircraft (e.g., when charging connector 108 (and/or associated charging station) is the closest recharging site to electric aircraft which may be in danger of losing power).

Referring now to FIG. 1B, an exemplary embodiment of an immutable sequential listing 180 is illustrated. An “immutable sequential listing,” as used in this disclosure, is a data structure that places data entries in a fixed sequential arrangement, such as a temporal sequence of entries and/or blocks thereof, where the sequential arrangement, once established, cannot be altered or reordered. An immutable sequential listing may be, include and/or implement an immutable ledger, where data entries that have been posted to the immutable sequential listing cannot be altered. Authentication, in accordance with certain embodiments of the present disclosure, may include evaluating a “digitally signed assertion,” from an “immutable sequential listing,” that contains or represents one or more data for authentication (credentials, authorization token, etc.). An authentication decision and/or event may be recorded using a digitally signed assertion in the listing.

Still referring to FIG. 1B, data elements are listing in immutable sequential listing 180; data elements may include any form of data, including textual data, image data, encrypted data, cryptographically hashed data, and the like. Data elements may include, without limitation, one or more at least a digitally signed assertions. In one embodiment, a digitally signed assertion 184 is a collection of textual data signed using a secure proof as described in further detail below; secure proof may include, without limitation, a digital signature as described above. Collection of textual data may contain any textual data, including without limitation American Standard Code for Information Interchange (ASCII), Unicode, or similar computer-encoded textual data, any alphanumeric data, punctuation, diacritical mark, or any character or other marking used in any writing system to convey information, in any form, including any plaintext or cyphertext data; in an embodiment, collection of textual data may be encrypted, or may be a hash of other data, such as a root or node of a Merkle tree or hash tree, or a hash of any other information desired to be recorded in some fashion using a digitally signed assertion 184. In an embodiment, collection of textual data states that the owner of a certain transferable item represented in a digitally signed assertion 184 register is transferring that item to the owner of an address. A digitally signed assertion 184 may be signed by a digital signature created using the private key associated with the owner's public key, as described above.

Still referring to FIG. 1B, a digitally signed assertion 184 may describe a transfer of virtual currency, such as crypto-currency as described below. The virtual currency may be a digital currency. Item of value may be a transfer of trust, for instance represented by a statement vouching for the identity or trustworthiness of the first entity. Item of value may be an interest in a fungible negotiable financial instrument representing ownership in a public or private corporation, a creditor relationship with a governmental body or a corporation, rights to ownership represented by an option, derivative financial instrument, commodity, debt-backed security such as a bond or debenture or other security as described in further detail below. A resource may be a physical machine e.g. a ride share vehicle or any other asset. A digitally signed assertion 184 may describe the transfer of a physical good; for instance, a digitally signed assertion 184 may describe the sale of a product. In some embodiments, a transfer nominally of one item may be used to represent a transfer of another item; for instance, a transfer of virtual currency may be interpreted as representing a transfer of an access right; conversely, where the item nominally transferred is something other than virtual currency, the transfer itself may still be treated as a transfer of virtual currency, having value that depends on many potential factors including the value of the item nominally transferred and the monetary value attendant to having the output of the transfer moved into a particular user's control. The item of value may be associated with a digitally signed assertion 184 by means of an exterior protocol, such as the COLORED COINS created according to protocols developed by The Colored Coins Foundation, the MASTERCOIN protocol developed by the Mastercoin Foundation, or the ETHEREUM platform offered by the Stiftung Ethereum Foundation of Baar, Switzerland, the Thunder protocol developed by Thunder Consensus, or any other protocol.

Still referring to FIG. 1B, in one embodiment, an address is a textual datum identifying the recipient of virtual currency or another item of value in a digitally signed assertion 184. In some embodiments, address is linked to a public key, the corresponding private key of which is owned by the recipient of a digitally signed assertion 184. For instance, address may be the public key. Address may be a representation, such as a hash, of the public key. Address may be linked to the public key in memory of a computing device, for instance via a “wallet shortener” protocol. Where address is linked to a public key, a transferee in a digitally signed assertion 184 may record a subsequent a digitally signed assertion 184 transferring some or all of the value transferred in the first a digitally signed assertion 184 to a new address in the same manner. A digitally signed assertion 184 may contain textual information that is not a transfer of some item of value in addition to, or as an alternative to, such a transfer. For instance, as described in further detail below, a digitally signed assertion 184 may indicate a confidence level associated with a distributed storage node as described in further detail below.

In an embodiment, and still referring to FIG. 1B immutable sequential listing 180 records a series of at least a posted content in a way that preserves the order in which the at least a posted content took place. Temporally sequential listing may be accessible at any of various security settings; for instance, and without limitation, temporally sequential listing may be readable and modifiable publicly, may be publicly readable but writable only by entities and/or devices having access privileges established by password protection, confidence level, or any device authentication procedure or facilities described herein, or may be readable and/or writable only by entities and/or devices having such access privileges. Access privileges may exist in more than one level, including, without limitation, a first access level or community of permitted entities and/or devices having ability to read, and a second access level or community of permitted entities and/or devices having ability to write; first and second community may be overlapping or non-overlapping. In an embodiment, posted content and/or immutable sequential listing 180 may be stored as one or more zero knowledge sets (ZKS), Private Information Retrieval (PIR) structure, or any other structure that allows checking of membership in a set by querying with specific properties. Such database may incorporate protective measures to ensure that malicious actors may not query the database repeatedly in an effort to narrow the members of a set to reveal uniquely identifying information of a given posted content.

Still referring to FIG. 1B, immutable sequential listing 180 may preserve the order in which the at least a posted content took place by listing them in chronological order; alternatively or additionally, immutable sequential listing 180 may organize digitally signed assertions 184 into sub-listings 188 such as “blocks” in a blockchain, which may be themselves collected in a temporally sequential order; digitally signed assertions 184 within a sub-listing 188 may or may not be temporally sequential. The ledger may preserve the order in which at least a posted content took place by listing them in sub-listings 188 and placing the sub-listings 188 in chronological order. The immutable sequential listing 180 may be a distributed, consensus-based ledger, such as those operated according to the protocols promulgated by Ripple Labs, Inc., of San Francisco, Calif., or the Stellar Development Foundation, of San Francisco, Calif., or of Thunder Consensus. In some embodiments, the ledger is a secured ledger; in one embodiment, a secured ledger is a ledger having safeguards against alteration by unauthorized parties. The ledger may be maintained by a proprietor, such as a system administrator on a server, that controls access to the ledger; for instance, the user account controls may allow contributors to the ledger to add at least a posted content to the ledger, but may not allow any users to alter at least a posted content that have been added to the ledger. In some embodiments, ledger is cryptographically secured; in one embodiment, a ledger is cryptographically secured where each link in the chain contains encrypted or hashed information that makes it practically infeasible to alter the ledger without betraying that alteration has taken place, for instance by requiring that an administrator or other party sign new additions to the chain with a digital signature. Immutable sequential listing 180 may be incorporated in, stored in, or incorporate, any suitable data structure, including without limitation any database, datastore, file structure, distributed hash table, directed acyclic graph or the like. In some embodiments, the timestamp of an entry is cryptographically secured and validated via trusted time, either directly on the chain or indirectly by utilizing a separate chain. In one embodiment the validity of timestamp is provided using a time stamping authority as described in the RFC 3161 standard for trusted timestamps, or in the ANSI ASC x9.95 standard. In another embodiment, the trusted time ordering is provided by a group of entities collectively acting as the time stamping authority with a requirement that a threshold number of the group of authorities sign the timestamp.

In some embodiments, and with continued reference to FIG. 1B, immutable sequential listing 180, once formed, may be inalterable by any party, no matter what access rights that party possesses. For instance, immutable sequential listing 180 may include a hash chain, in which data is added during a successive hashing process to ensure non-repudiation. Immutable sequential listing 180 may include a block chain. In one embodiment, a block chain is immutable sequential listing 180 that records one or more new at least a posted content in a data item known as a sub-listing 188 or “block.” An example of a block chain is the BITCOIN block chain used to record BITCOIN transactions and values. Sub-listings 188 may be created in a way that places the sub-listings 188 in chronological order and link each sub-listing 188 to a previous sub-listing 188 in the chronological order so that any computing device may traverse the sub-listings 188 in reverse chronological order to verify any at least a posted content listed in the block chain. Each new sub-listing 188 may be required to contain a cryptographic hash describing the previous sub-listing 188. In some embodiments, the block chain contains a single first sub-listing 188 sometimes known as a “genesis block.”

Still referring to FIG. 1B, the creation of a new sub-listing 188 may be computationally expensive; for instance, the creation of a new sub-listing 188 may be designed by a “proof of work” protocol accepted by all participants in forming the immutable sequential listing 180 to take a powerful set of computing devices a certain period of time to produce. Where one sub-listing 188 takes less time for a given set of computing devices to produce the sub-listing 188 protocol may adjust the algorithm to produce the next sub-listing 188 so that it will require more steps; where one sub-listing 188 takes more time for a given set of computing devices to produce the sub-listing 188 protocol may adjust the algorithm to produce the next sub-listing 188 so that it will require fewer steps. As an example, protocol may require a new sub-listing 188 to contain a cryptographic hash describing its contents; the cryptographic hash may be required to satisfy a mathematical condition, achieved by having the sub-listing 188 contain a number, called a nonce, whose value is determined after the fact by the discovery of the hash that satisfies the mathematical condition. Continuing the example, the protocol may be able to adjust the mathematical condition so that the discovery of the hash describing a sub-listing 188 and satisfying the mathematical condition requires more or less steps, depending on the outcome of the previous hashing attempt. Mathematical condition, as an example, might be that the hash contains a certain number of leading zeros and a hashing algorithm that requires more steps to find a hash containing a greater number of leading zeros, and fewer steps to find a hash containing a lesser number of leading zeros. In some embodiments, production of a new sub-listing 188 according to the protocol is known as “mining.” The creation of a new sub-listing 188 may be designed by a “proof of stake” protocol as will be apparent to those skilled in the art upon reviewing the entirety of this disclosure.

Continuing to refer to FIG. 1B, in some embodiments, protocol also creates an incentive to mine new sub-listings 188. The incentive may be financial; for instance, successfully mining a new sub-listing 188 may result in the person or entity that mines the sub-listing 188 receiving a predetermined amount of currency. The currency may be fiat currency. Currency may be cryptocurrency as defined below. In other embodiments, incentive may be redeemed for particular products or services; the incentive may be a gift certificate with a particular business, for instance. In some embodiments, incentive is sufficiently attractive to cause participants to compete for the incentive by trying to race each other to the creation of sub-listings 188 Each sub-listing 188 created in immutable sequential listing 180 may contain a record or at least a posted content describing one or more addresses that receive an incentive, such as virtual currency, as the result of successfully mining the sub-listing 188.

With continued reference to FIG. 1B, where two entities simultaneously create new sub-listings 188, immutable sequential listing 180 may develop a fork; protocol may determine which of the two alternate branches in the fork is the valid new portion of the immutable sequential listing 180 by evaluating, after a certain amount of time has passed, which branch is longer. “Length” may be measured according to the number of sub-listings 188 in the branch. Length may be measured according to the total computational cost of producing the branch. Protocol may treat only at least a posted content contained the valid branch as valid at least a posted content. When a branch is found invalid according to this protocol, at least a posted content registered in that branch may be recreated in a new sub-listing 188 in the valid branch; the protocol may reject “double spending” at least a posted content that transfer the same virtual currency that another at least a posted content in the valid branch has already transferred. As a result, in some embodiments the creation of fraudulent at least a posted content requires the creation of a longer immutable sequential listing 180 branch by the entity attempting the fraudulent at least a posted content than the branch being produced by the rest of the participants; as long as the entity creating the fraudulent at least a posted content is likely the only one with the incentive to create the branch containing the fraudulent at least a posted content, the computational cost of the creation of that branch may be practically infeasible, guaranteeing the validity of all at least a posted content in the immutable sequential listing 180.

Still referring to FIG. 1B, additional data linked to at least a posted content may be incorporated in sub-listings 188 in the immutable sequential listing 180; for instance, data may be incorporated in one or more fields recognized by block chain protocols that permit a person or computer forming a at least a posted content to insert additional data in the immutable sequential listing 180. In some embodiments, additional data is incorporated in an unspendable at least a posted content field. For instance, the data may be incorporated in an OP RETURN within the BITCOIN block chain. In other embodiments, additional data is incorporated in one signature of a multi-signature at least a posted content. In an embodiment, a multi-signature at least a posted content is at least a posted content to two or more addresses. In some embodiments, the two or more addresses are hashed together to form a single address, which is signed in the digital signature of the at least a posted content. In other embodiments, the two or more addresses are concatenated. In some embodiments, two or more addresses may be combined by a more complicated process, such as the creation of a Merkle tree or the like. In some embodiments, one or more addresses incorporated in the multi-signature at least a posted content are typical crypto-currency addresses, such as addresses linked to public keys as described above, while one or more additional addresses in the multi-signature at least a posted content contain additional data related to the at least a posted content; for instance, the additional data may indicate the purpose of the at least a posted content, aside from an exchange of virtual currency, such as the item for which the virtual currency was exchanged. In some embodiments, additional information may include network statistics for a given node of network, such as a distributed storage node, e.g. the latencies to nearest neighbors in a network graph, the identities or identifying information of neighboring nodes in the network graph, the trust level and/or mechanisms of trust (e.g. certificates of physical encryption keys, certificates of software encryption keys, (in non-limiting example certificates of software encryption may indicate the firmware version, manufacturer, hardware version and the like), certificates from a trusted third party, certificates from a decentralized anonymous authentication procedure, and other information quantifying the trusted status of the distributed storage node) of neighboring nodes in the network graph, IP addresses, GPS coordinates, and other information informing location of the node and/or neighboring nodes, geographically and/or within the network graph. In some embodiments, additional information may include history and/or statistics of neighboring nodes with which the node has interacted. In some embodiments, this additional information may be encoded directly, via a hash, hash tree or other encoding.

With continued reference to FIG. 1B, in some embodiments, virtual currency is traded as a crypto-currency. In one embodiment, a crypto-currency is a digital, currency such as Bitcoins, Peercoins, Namecoins, and Litecoins. Crypto-currency may be a clone of another crypto-currency. The crypto-currency may be an “alt-coin.” Crypto-currency may be decentralized, with no particular entity controlling it; the integrity of the crypto-currency may be maintained by adherence by its participants to established protocols for exchange and for production of new currency, which may be enforced by software implementing the crypto-currency. Crypto-currency may be centralized, with its protocols enforced or hosted by a particular entity. For instance, crypto-currency may be maintained in a centralized ledger, as in the case of the XRP currency of Ripple Labs, Inc., of San Francisco, Calif. In lieu of a centrally controlling authority, such as a national bank, to manage currency values, the number of units of a particular crypto-currency may be limited; the rate at which units of crypto-currency enter the market may be managed by a mutually agreed-upon process, such as creating new units of currency when mathematical puzzles are solved, the degree of difficulty of the puzzles being adjustable to control the rate at which new units enter the market. Mathematical puzzles may be the same as the algorithms used to make productions of sub-listings 188 in a block chain computationally challenging; the incentive for producing sub-listings 188 may include the grant of new crypto-currency to the miners. Quantities of crypto-currency may be exchanged using at least a posted content as described above.

Referring now to FIG. 2, an exemplary embodiment of an electric aircraft 200 which may be used in conjunction with, incorporate and/or include a system for authentication of an electric aircraft for recharging (or charging) (e.g. system 100 of FIG. 1A) is illustrated. Electric aircraft 200, and any of its features, may be used in conjunction with any of the embodiments of the present disclosure. Electric aircraft 200 may include any of the aircrafts as disclosed in the present disclosure. In an embodiment, electric aircraft 200 may be an electric vertical takeoff and landing (eVTOL) aircraft. As used in this disclosure, an “aircraft” is any vehicle that may fly by gaining support from the air. As a non-limiting example, aircraft may include airplanes, helicopters, commercial, personal and/or recreational aircrafts, instrument flight aircrafts, drones, electric aircrafts, hybrid-electric aircrafts, electric aerial vehicles, airliners, rotorcrafts, vertical takeoff and landing aircrafts, jets, airships, blimps, gliders, paramotors, quad-copters, unmanned aerial vehicles (UAVs) and the like. As used in this disclosure, an “electric aircraft” is an electrically powered aircraft such as one powered by one or more electric motors or the like. In some embodiments, electrically powered (or electric) aircraft may be an electric vertical takeoff and landing (eVTOL) aircraft. In some embodiments, electric aircraft may include a hybrid-electric aircraft, for example and without limitation, an aircraft that may be powered by both electricity and combustion (e.g. internal combustion). Electric aircraft may be capable of rotor-based cruising flight, rotor-based takeoff, rotor-based landing, fixed-wing cruising flight, airplane-style takeoff, airplane-style landing, and/or any combination thereof. Electric aircraft may include one or more manned and/or unmanned aircrafts. Electric aircraft may include one or more all-electric short takeoff and landing (eSTOL) aircrafts. For example, and without limitation, eSTOL aircrafts may accelerate the plane to a flight speed on takeoff and decelerate the plane after landing. In an embodiment, and without limitation, electric aircraft may be configured with an electric propulsion assembly. Including one or more propulsion and/or flight components. Electric propulsion assembly may include any electric propulsion assembly (or system) as described in U.S. Nonprovisional application Ser. No. 16/703,225, filed on Dec. 4, 2019, and entitled “AN INTEGRATED ELECTRIC PROPULSION ASSEMBLY,” the entirety of which is incorporated herein by reference.

Still referring to FIG. 2, as used in this disclosure, a “vertical take-off and landing (VTOL) aircraft” is one that can hover, take off, and land vertically. An “electric vertical takeoff and landing aircraft” or “eVTOL aircraft”, as used in this disclosure, is an electrically powered VTOL aircraft typically using an energy source, of a plurality of energy sources to power the aircraft. In order to optimize the power and energy necessary to propel the aircraft, eVTOL may be capable of rotor-based cruising flight, rotor-based takeoff, rotor-based landing, fixed-wing cruising flight, airplane-style takeoff, airplane style landing, and/or any combination thereof. Rotor-based flight, as described herein, is where the aircraft generates lift and propulsion by way of one or more powered rotors or blades coupled with an engine, such as a “quad copter,” multi-rotor helicopter, or other vehicle that maintains its lift primarily using downward thrusting propulsors. “Fixed-wing flight”, as described herein, is where the aircraft is capable of flight using wings and/or foils that generate lift caused by the aircraft's forward airspeed and the shape of the wings and/or foils, such as airplane-style flight.

Still referring to FIG. 2, in an embodiment, electric aircraft 200 may be a hybrid-electric aircraft and may be powered by a hybrid-electric power system. A hybrid-electric vehicle (HEV) or aircraft, as used in the present disclosure, is a type of hybrid vehicle or aircraft that combines a conventional internal combustion engine (ICE) system with an electric propulsion system.

Still referring to FIG. 2, electric aircraft 200, in some embodiments, may generally include a fuselage 204, a flight component 208 (or a plurality of flight components 208), a pilot control 220, a sensor 228 (or a plurality of sensors 208) and flight controller 124. In one embodiment, flight components 208 may include at least a lift component 212 (or a plurality of lift components 212) and at least a pusher component 216 (or a plurality of pusher components 216). Sensor(s) 228 may also be referred to as aircraft sensor(s) herein and may be similar to or the same as the aircraft sensor(s) of FIG. 1A.

Still referring to FIG. 2, as used in this disclosure a “fuselage” is the main body of an aircraft, or in other words, the entirety of the aircraft except for the cockpit, nose, wings, empennage, nacelles, any and all control surfaces, and generally contains an aircraft's payload. Fuselage 204 may include structural elements that physically support a shape and structure of an aircraft. Structural elements may take a plurality of forms, alone or in combination with other types. Structural elements may vary depending on a construction type of aircraft such as without limitation a fuselage 204. Fuselage 204 may comprise a truss structure. A truss structure may be used with a lightweight aircraft and comprises welded steel tube trusses. A “truss,” as used in this disclosure, is an assembly of beams that create a rigid structure, often in combinations of triangles to create three-dimensional shapes. A truss structure may alternatively comprise wood construction in place of steel tubes, or a combination thereof. In embodiments, structural elements may comprise steel tubes and/or wood beams. In an embodiment, and without limitation, structural elements may include an aircraft skin. Aircraft skin may be layered over the body shape constructed by trusses. Aircraft skin may comprise a plurality of materials such as plywood sheets, aluminum, fiberglass, and/or carbon fiber.

Still referring to FIG. 2, it should be noted that an illustrative embodiment is presented only, and this disclosure in no way limits the form or construction method of any of the aircrafts as disclosed herein. In embodiments, fuselage 204 may be configurable based on the needs of the aircraft per specific mission or objective. The general arrangement of components, structural elements, and hardware associated with storing and/or moving a payload may be added or removed from fuselage 204 as needed, whether it is stowed manually, automatedly, or removed by personnel altogether. Fuselage 204 may be configurable for a plurality of storage options. Bulkheads and dividers may be installed and uninstalled as needed, as well as longitudinal dividers where necessary. Bulkheads and dividers may be installed using integrated slots and hooks, tabs, boss and channel, or hardware like bolts, nuts, screws, nails, clips, pins, and/or dowels, to name a few. Fuselage 204 may also be configurable to accept certain specific cargo containers, or a receptable that can, in turn, accept certain cargo containers.

Still referring to FIG. 2, electric aircraft 200 may include a plurality of laterally extending elements attached to fuselage 204. As used in this disclosure a “laterally extending element” is an element that projects essentially horizontally from fuselage, including an outrigger, a spar, and/or a fixed wing that extends from fuselage. Wings may be structures which include airfoils configured to create a pressure differential resulting in lift. Wings may generally be disposed on the left and right sides of the aircraft symmetrically, at a point between nose and empennage. Wings may comprise a plurality of geometries in planform view, swept swing, tapered, variable wing, triangular, oblong, elliptical, square, among others. A wing's cross section geometry may comprise an airfoil. An “airfoil” as used in this disclosure is a shape specifically designed such that a fluid flowing above and below it exert differing levels of pressure against the top and bottom surface. In embodiments, the bottom surface of an aircraft can be configured to generate a greater pressure than does the top, resulting in lift. Laterally extending element may comprise differing and/or similar cross-sectional geometries over its cord length or the length from wing tip to where wing meets the aircraft's body. One or more wings may be symmetrical about the aircraft's longitudinal plane, which comprises the longitudinal or roll axis reaching down the center of the aircraft through the nose and empennage, and the plane's yaw axis. Laterally extending element may comprise controls surfaces configured to be commanded by a pilot or pilots to change a wing's geometry and therefore its interaction with a fluid medium, like air. Control surfaces may comprise flaps, ailerons, tabs, spoilers, and slats, among others. The control surfaces may dispose on the wings in a plurality of locations and arrangements and in embodiments may be disposed at the leading and trailing edges of the wings, and may be configured to deflect up, down, forward, aft, or a combination thereof. An aircraft, including a dual-mode aircraft may comprise a combination of control surfaces to perform maneuvers while flying or on ground. In some embodiments, winglets may be provided at terminal ends of the wings which can provide improved aerodynamic efficiency and stability in certain flight situations. In some embodiments, the wings may be foldable to provide a compact aircraft profile, for example, for storage, parking and/or in certain flight modes.

Still referring to FIG. 2, electric aircraft 200 may include a plurality of flight components 208. As used in this disclosure a “flight component” is a component that promotes flight and guidance of an aircraft. Flight component 208 may include power sources, control links to one or more elements, fuses, and/or mechanical couplings used to drive and/or control any other flight component. Flight component 208 may include a motor that operates to move one or more flight control components, to drive one or more propulsors, or the like. A motor may be driven by direct current (DC) electric power and may include, without limitation, brushless DC electric motors, switched reluctance motors, induction motors, or any combination thereof. A motor may also include electronic speed controllers or other components for regulating motor speed, rotation direction, and/or dynamic braking. Flight component 208 may include an energy source. An energy source may include, for example, a generator, a photovoltaic device, a fuel cell such as a hydrogen fuel cell, direct methanol fuel cell, and/or solid oxide fuel cell, an electric energy storage device (e.g. a capacitor, an inductor, and/or a battery). An energy source may also include a battery cell, or a plurality of battery cells connected in series into a module and each module connected in series or in parallel with other modules. Configuration of an energy source containing connected modules may be designed to meet an energy or power requirement and may be designed to fit within a designated footprint in an electric aircraft.

Still referring to FIG. 2, in an embodiment, flight component 208 may be mechanically coupled to an aircraft. As used herein, a person of ordinary skill in the art would understand “mechanically coupled” to mean that at least a portion of a device, component, or circuit is connected to at least a portion of the aircraft via a mechanical coupling. Said mechanical coupling can include, for example, rigid coupling, such as beam coupling, bellows coupling, bushed pin coupling, constant velocity, split-muff coupling, diaphragm coupling, disc coupling, donut coupling, elastic coupling, flexible coupling, fluid coupling, gear coupling, grid coupling, hirth joints, hydrodynamic coupling, jaw coupling, magnetic coupling, Oldham coupling, sleeve coupling, tapered shaft lock, twin spring coupling, rag joint coupling, universal joints, or any combination thereof. In an embodiment, mechanical coupling may be used to connect the ends of adjacent parts and/or objects of an electric aircraft. Further, in an embodiment, mechanical coupling may be used to join two pieces of rotating electric aircraft components.

Still referring to FIG. 2, in an embodiment, plurality of flight components 208 of aircraft 200 may include at least a lift component 212 and at least a pusher component 216. Flight component 208 may include a propulsor, a propeller, a motor, rotor, a rotating element, electrical energy source, battery, and the like, among others. Each flight component may be configured to generate lift and flight of electric aircraft. In some embodiments, flight component 208 may include one or more lift components 212, one or more pusher components 216, one or more battery packs including one or more batteries or cells, and one or more electric motors. Flight component 208 may include a propulsor. As used in this disclosure a “propulsor component” or “propulsor” is a component and/or device used to propel a craft by exerting force on a fluid medium, which may include a gaseous medium such as air or a liquid medium such as water. In an embodiment, when a propulsor twists and pulls air behind it, it may, at the same time, push an aircraft forward with an amount of force and/or thrust. More air pulled behind an aircraft results in greater thrust with which the aircraft is pushed forward. Propulsor component may include any device or component that consumes electrical power on demand to propel an electric aircraft in a direction or other vehicle while on ground or in-flight.

Still referring to FIG. 2, in some embodiments, lift component 212 may include a propulsor, a propeller, a blade, a motor, a rotor, a rotating element, an aileron, a rudder, arrangements thereof, combinations thereof, and the like. Each lift component 212, when a plurality is present, of plurality of flight components 208 is configured to produce, in an embodiment, substantially upward and/or vertical thrust such that aircraft moves upward.

With continued reference to FIG. 2, as used in this disclosure a “lift component” is a component and/or device used to propel a craft upward by exerting downward force on a fluid medium, which may include a gaseous medium such as air or a liquid medium such as water. Lift component 212 may include any device or component that consumes electrical power on demand to propel an electric aircraft in a direction or other vehicle while on ground or in-flight. For example, and without limitation, lift component 212 may include a rotor, propeller, paddle wheel and the like thereof, wherein a rotor is a component that produces torque along the longitudinal axis, and a propeller produces torque along the vertical axis. In an embodiment, lift component 212 includes a plurality of blades. As used in this disclosure a “blade” is a propeller that converts rotary motion from an engine or other power source into a swirling slipstream. In an embodiment, blade may convert rotary motion to push the propeller forwards or backwards. In an embodiment lift component 212 may include a rotating power-driven hub, to which are attached several radial airfoil-section blades such that the whole assembly rotates about a longitudinal axis. Blades may be configured at an angle of attack. In an embodiment, and without limitation, angle of attack may include a fixed angle of attack. As used in this disclosure a “fixed angle of attack” is fixed angle between a chord line of a blade and relative wind. As used in this disclosure a “fixed angle” is an angle that is secured and/or unmovable from the attachment point. In an embodiment, and without limitation, angle of attack may include a variable angle of attack. As used in this disclosure a “variable angle of attack” is a variable and/or moveable angle between a chord line of a blade and relative wind. As used in this disclosure a “variable angle” is an angle that is moveable from an attachment point. In an embodiment, angle of attack be configured to produce a fixed pitch angle. As used in this disclosure a “fixed pitch angle” is a fixed angle between a cord line of a blade and the rotational velocity direction. In an embodiment fixed angle of attack may be manually variable to a few set positions to adjust one or more lifts of the aircraft prior to flight. In an embodiment, blades for an aircraft are designed to be fixed to their hub at an angle similar to the thread on a screw makes an angle to the shaft; this angle may be referred to as a pitch or pitch angle which will determine a speed of forward movement as the blade rotates.

In an embodiment, and still referring to FIG. 2, lift component 212 may be configured to produce a lift. As used in this disclosure a “lift” is a perpendicular force to the oncoming flow direction of fluid surrounding the surface. For example, and without limitation relative air speed may be horizontal to the aircraft, wherein lift force may be a force exerted in a vertical direction, directing the aircraft upwards. In an embodiment, and without limitation, lift component 212 may produce lift as a function of applying a torque to lift component. As used in this disclosure a “torque” is a measure of force that causes an object to rotate about an axis in a direction. For example, and without limitation, torque may rotate an aileron and/or rudder to generate a force that may adjust and/or affect altitude, airspeed velocity, groundspeed velocity, direction during flight, and/or thrust. For example, one or more flight components 208 such as a power source(s) may apply a torque on lift component 212 to produce lift.

In an embodiment and still referring to FIG. 2, a plurality of lift components 212 of plurality of flight components 208 may be arranged in a quad copter orientation. As used in this disclosure a “quad copter orientation” is at least a lift component oriented in a geometric shape and/or pattern, wherein each of the lift components is located along a vertex of the geometric shape. For example, and without limitation, a square quad copter orientation may have four lift propulsor components oriented in the geometric shape of a square, wherein each of the four lift propulsor components are located along the four vertices of the square shape. As a further non-limiting example, a hexagonal quad copter orientation may have six lift components oriented in the geometric shape of a hexagon, wherein each of the six lift components are located along the six vertices of the hexagon shape. In an embodiment, and without limitation, quad copter orientation may include a first set of lift components and a second set of lift components, wherein the first set of lift components and the second set of lift components may include two lift components each, wherein the first set of lift components and a second set of lift components are distinct from one another. For example, and without limitation, the first set of lift components may include two lift components that rotate in a clockwise direction, wherein the second set of lift propulsor components may include two lift components that rotate in a counterclockwise direction. In an embodiment, and without limitation, the first set of lift components may be oriented along a line oriented 45° from the longitudinal axis of aircraft 200. In another embodiment, and without limitation, the second set of lift components may be oriented along a line oriented 135° from the longitudinal axis, wherein the first set of lift components line and the second set of lift components are perpendicular to each other.

Still referring to FIG. 2, pusher component 216 and lift component 212 (of flight component(s) 208) may include any such components and related devices as disclosed in U.S. Nonprovisional application Ser. No. 16/427,298, filed on May 30, 2019, entitled “SELECTIVELY DEPLOYABLE HEATED PROPULSOR SYSTEM,” U.S. Nonprovisional application Ser. No. 16/703,225, filed on Dec. 4, 2019, entitled “AN INTEGRATED ELECTRIC PROPULSION ASSEMBLY,” U.S. Nonprovisional application Ser. No. 16/910,255, filed on Jun. 24, 2020, entitled “AN INTEGRATED ELECTRIC PROPULSION ASSEMBLY,” U.S. Nonprovisional application Ser. No. 17/319,155, filed on May 13, 2021, entitled “AIRCRAFT HAVING REVERSE THRUST CAPABILITIES,” U.S. Nonprovisional application Ser. No. 16/929,206, filed on Jul. 15, 2020, entitled “A HOVER AND THRUST CONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/001,845, filed on Aug. 25, 2020, entitled “A HOVER AND THRUST CONTROL ASSEMBLY FOR DUAL-MODE AIRCRAFT,” U.S. Nonprovisional application Ser. No. 17/186,079, filed on Feb. 26, 2021, entitled “METHODS AND SYSTEM FOR ESTIMATING PERCENTAGE TORQUE PRODUCED BY A PROPULSOR CONFIGURED FOR USE IN AN ELECTRIC AIRCRAFT,” and U.S. Nonprovisional application Ser. No. 17/321,662, filed on May 17, 2021, entitled “AIRCRAFT FOR FIXED PITCH LIFT,” the entirety of each one of which is incorporated herein by reference. Any aircrafts, including electric and eVTOL aircrafts, as disclosed in any of these applications may efficaciously be utilized with any of the embodiments as disclosed herein, as needed or desired. Any flight controllers as disclosed in any of these applications may efficaciously be utilized with any of the embodiments as disclosed herein, as needed or desired.

Still referring to FIG. 2, pusher component 216 may include a propulsor, a propeller, a blade, a motor, a rotor, a rotating element, an aileron, a rudder, arrangements thereof, combinations thereof, and the like. Each pusher component 216, when a plurality is present, of the plurality of flight components 208 is configured to produce, in an embodiment, substantially forward and/or horizontal thrust such that the aircraft moves forward.

Still referring to FIG. 2, as used in this disclosure a “pusher component” is a component that pushes and/or thrusts an aircraft through a medium. As a non-limiting example, pusher component 216 may include a pusher propeller, a paddle wheel, a pusher motor, a pusher propulsor, and the like. Additionally, or alternatively, pusher flight component may include a plurality of pusher flight components. Pusher component 216 is configured to produce a forward thrust. As a non-limiting example, forward thrust may include a force to force aircraft to in a horizontal direction along the longitudinal axis. As a further non-limiting example, pusher component 216 may twist and/or rotate to pull air behind it and, at the same time, push aircraft 200 forward with an equal amount of force. In an embodiment, and without limitation, the more air forced behind aircraft, the greater the thrust force with which the aircraft is pushed horizontally will be. In another embodiment, and without limitation, forward thrust may force aircraft 200 through the medium of relative air. Additionally or alternatively, plurality of flight components 208 may include one or more puller components. As used in this disclosure a “puller component” is a component that pulls and/or tows an aircraft through a medium. As a non-limiting example, puller component may include a flight component such as a puller propeller, a puller motor, a tractor propeller, a puller propulsor, and the like. Additionally, or alternatively, puller component may include a plurality of puller flight components.

Still referring to FIG. 2, as used in this disclosure a “power source” is a source that powers, drives and/or controls any flight component and/or other aircraft component. For example, and without limitation power source may include a motor that operates to move one or more lift components 212 and/or one or more pusher components 216, to drive one or more blades, or the like thereof. Motor(s) may be driven by direct current (DC) electric power and may include, without limitation, brushless DC electric motors, switched reluctance motors, induction motors, or any combination thereof. Motor(s) may also include electronic speed controllers or other components for regulating motor speed, rotation direction, and/or dynamic braking. A “motor” as used in this disclosure is any machine that converts non-mechanical energy into mechanical energy. An “electric motor” as used in this disclosure is any machine that converts electrical energy into mechanical energy.

Still referring to FIG. 2, in an embodiment, aircraft 200 may include a pilot control 220. As used in this disclosure, a “pilot control” is a mechanism or means which allows a pilot to monitor and control operation of aircraft such as its flight components (for example, and without limitation, pusher component, lift component and other components such as propulsion components). For example, and without limitation, pilot control 220 may include a collective, inceptor, foot bake, steering and/or control wheel, control stick, pedals, throttle levers, and the like. Pilot control 220 may be configured to translate a pilot's desired torque for each flight component of the plurality of flight components, such as and without limitation, pusher component 216 and lift component 212. Pilot control 220 may be configured to control, via inputs and/or signals such as from a pilot, the pitch, roll, and yaw of the aircraft. Pilot control may be available onboard aircraft or remotely located from it, as needed or desired.

Still referring to FIG. 2, as used in this disclosure a “collective control” or “collective” is a mechanical control of an aircraft that allows a pilot to adjust and/or control the pitch angle of plurality of flight components 208. For example and without limitation, collective control may alter and/or adjust the pitch angle of all of the main rotor blades collectively. For example, and without limitation pilot control 220 may include a yoke control. As used in this disclosure a “yoke control” is a mechanical control of an aircraft to control the pitch and/or roll. For example and without limitation, yoke control may alter and/or adjust the roll angle of aircraft 200 as a function of controlling and/or maneuvering ailerons. In an embodiment, pilot control 220 may include one or more foot-brakes, control sticks, pedals, throttle levels, and the like thereof. In another embodiment, and without limitation, pilot control 220 may be configured to control a principal axis of the aircraft. As used in this disclosure a “principal axis” is an axis in a body representing one three dimensional orientations. For example, and without limitation, principal axis or more yaw, pitch, and/or roll axis. Principal axis may include a yaw axis. As used in this disclosure a “yaw axis” is an axis that is directed towards the bottom of aircraft, perpendicular to the wings. For example, and without limitation, a positive yawing motion may include adjusting and/or shifting nose of aircraft 200 to the right. Principal axis may include a pitch axis. As used in this disclosure a “pitch axis” is an axis that is directed towards the right laterally extending wing of aircraft. For example, and without limitation, a positive pitching motion may include adjusting and/or shifting nose of aircraft 200 upwards. Principal axis may include a roll axis. As used in this disclosure a “roll axis” is an axis that is directed longitudinally towards nose of aircraft, parallel to fuselage. For example, and without limitation, a positive rolling motion may include lifting the left and lowering the right wing concurrently. Pilot control 220 may be configured to modify a variable pitch angle. For example, and without limitation, pilot control 220 may adjust one or more angles of attack of a propulsor or propeller.

Still referring to FIG. 2, aircraft 200 may include at least a sensor (or aircraft sensor) 228. Sensor 228 may include any sensor or noise monitoring circuit described in this disclosure. Sensor 228, in some embodiments, may be communicatively connected or coupled to flight controller 124. Sensor 228 may be configured to sense a characteristic of pilot control 220. Sensor may be a device, module, and/or subsystem, utilizing any hardware, software, and/or any combination thereof to sense a characteristic and/or changes thereof, in an instant environment, for instance without limitation a pilot control 220, which the sensor is proximal to or otherwise in a sensed communication with, and transmit information associated with the characteristic, for instance without limitation digitized data. Sensor 228 may be mechanically and/or communicatively coupled to aircraft 200, including, for instance, to at least a pilot control 220. Sensor 228 may be configured to sense a characteristic associated with at least a pilot control 220. An environmental sensor may include without limitation one or more sensors used to detect ambient temperature, barometric pressure, and/or air velocity. Sensor 228 may include without limitation gyroscopes, accelerometers, inertial measurement unit (IMU), and/or magnetic sensors, one or more humidity sensors, one or more oxygen sensors, or the like. Additionally or alternatively, sensor 228 may include at least a geospatial sensor. Sensor 228 may be located inside aircraft, and/or be included in and/or attached to at least a portion of aircraft. Sensor may include one or more proximity sensors, displacement sensors, vibration sensors, and the like thereof. Sensor may be used to monitor the status of aircraft 200 for both critical and non-critical functions. Sensor may be incorporated into vehicle or aircraft or be remote.

Still referring to FIG. 2, in some embodiments, sensor (or aircraft sensor) 228 may be configured to sense a characteristic associated with any pilot control described in this disclosure. Non-limiting examples of sensor 228 may include an inertial measurement unit (IMU), an accelerometer, a gyroscope, a proximity sensor, a pressure sensor, a light sensor, a pitot tube, an air speed sensor, a position sensor, a speed sensor, a switch, a thermometer, a strain gauge, an acoustic sensor, and an electrical sensor. In some cases, sensor 228 may sense a characteristic as an analog measurement, for instance, yielding a continuously variable electrical potential indicative of the sensed characteristic. In these cases, sensor 228 may additionally comprise an analog to digital converter (ADC) as well as any additionally circuitry, such as without limitation a Wheatstone bridge, an amplifier, a filter, and the like. For instance, in some cases, sensor 228 may comprise a strain gage configured to determine loading of one or more aircraft components, for instance landing gear. Strain gage may be included within a circuit comprising a Wheatstone bridge, an amplified, and a bandpass filter to provide an analog strain measurement signal having a high signal to noise ratio, which characterizes strain on a landing gear member. An ADC may then digitize analog signal produces a digital signal that can then be transmitted other systems within aircraft 200, for instance without limitation a computing system, a pilot display, and a memory component. Alternatively or additionally, sensor 228 may sense a characteristic of a pilot control 220 digitally. For instance in some embodiments, sensor 228 may sense a characteristic through a digital means or digitize a sensed signal natively. In some cases, for example, sensor 228 may include a rotational encoder and be configured to sense a rotational position of a pilot control; in this case, the rotational encoder digitally may sense rotational “clicks” by any known method, such as without limitation magnetically, optically, and the like. Sensor 228 may include any of the sensors as disclosed in the present disclosure. Sensor 228 may include a plurality of sensors. Any of these sensors may be located at any suitable position in or on aircraft 200.

With continued reference to FIG. 2, in some embodiments, electric aircraft 200 includes, or may be coupled to or communicatively connected to, flight controller 124 which is described further with reference to FIG. 3. As used in this disclosure a “flight controller” is a computing device of a plurality of computing devices dedicated to data storage, security, distribution of traffic for load balancing, and flight instruction. In embodiments, flight controller may be installed in an aircraft, may control the aircraft remotely, and/or may include an element installed in the aircraft and a remote element in communication therewith. Flight controller 124, in an embodiment, is located within fuselage 204 of aircraft. In accordance with some embodiments, flight controller is configured to operate a vertical lift flight (upwards or downwards, that is, takeoff or landing), a fixed wing flight (forward or backwards), a transition between a vertical lift flight and a fixed wing flight, and a combination of a vertical lift flight and a fixed wing flight.

Still referring to FIG. 2, in an embodiment, and without limitation, flight controller 124 may be configured to operate a fixed-wing flight capability. A “fixed-wing flight capability” can be a method of flight wherein the plurality of laterally extending elements generate lift. For example, and without limitation, fixed-wing flight capability may generate lift as a function of an airspeed of aircraft 200 and one or more airfoil shapes of the laterally extending elements. As a further non-limiting example, flight controller 124 may operate the fixed-wing flight capability as a function of reducing applied torque on lift (propulsor) component 212. In an embodiment, and without limitation, an amount of lift generation may be related to an amount of forward thrust generated to increase airspeed velocity, wherein the amount of lift generation may be directly proportional to the amount of forward thrust produced. Additionally or alternatively, flight controller may include an inertia compensator. As used in this disclosure an “inertia compensator” is one or more computing devices, electrical components, logic circuits, processors, and the like there of that are configured to compensate for inertia in one or more lift (propulsor) components present in aircraft 100. Inertia compensator may alternatively or additionally include any computing device used as an inertia compensator as described in U.S. Nonprovisional application Ser. No. 17/106,557, filed on Nov. 30, 2020, and entitled “SYSTEM AND METHOD FOR FLIGHT CONTROL IN ELECTRIC AIRCRAFT,” the entirety of which is incorporated herein by reference. Flight controller 124 may efficaciously include any flight controllers as disclosed in U.S. Nonprovisional application Ser. No. 17/106,557, filed on Nov. 30, 2020, and entitled “SYSTEM AND METHOD FOR FLIGHT CONTROL IN ELECTRIC AIRCRAFT.”

In an embodiment, and still referring to FIG. 2, flight controller 124 may be configured to perform a reverse thrust command. As used in this disclosure a “reverse thrust command” is a command to perform a thrust that forces a medium towards the relative air opposing aircraft 100. Reverse thrust command may alternatively or additionally include any reverse thrust command as described in U.S. Nonprovisional application Ser. No. 17/319,155, filed on May 13, 2021, and entitled “AIRCRAFT HAVING REVERSE THRUST CAPABILITIES,” the entirety of which is incorporated herein by reference. In another embodiment, flight controller may be configured to perform a regenerative drag operation. As used in this disclosure a “regenerative drag operation” is an operating condition of an aircraft, wherein the aircraft has a negative thrust and/or is reducing in airspeed velocity. For example, and without limitation, regenerative drag operation may include a positive propeller speed and a negative propeller thrust. Regenerative drag operation may alternatively or additionally include any regenerative drag operation as described in U.S. Nonprovisional application Ser. No. 17/319,155. Flight controller 124 may efficaciously include any flight controllers as disclosed in U.S. Nonprovisional application Ser. No. 17/319,155, filed on May 13, 2021, and entitled “AIRCRAFT HAVING REVERSE THRUST CAPABILITIES,”.

In an embodiment, and still referring to FIG. 2, flight controller 124 may be configured to perform a corrective action as a function of a failure event. As used in this disclosure a “corrective action” is an action conducted by the plurality of flight components to correct and/or alter a movement of an aircraft. For example, and without limitation, a corrective action may include an action to reduce a yaw torque generated by a failure event. Additionally or alternatively, corrective action may include any corrective action as described in U.S. Nonprovisional application Ser. No. 17/222,539, filed on Apr. 5, 2021, and entitled “AIRCRAFT FOR SELF-NEUTRALIZING FLIGHT,” the entirety of which is incorporated herein by reference. As used in this disclosure a “failure event” is a failure of a lift component of the plurality of lift components. For example, and without limitation, a failure event may denote a rotation degradation of a rotor, a reduced torque of a rotor, and the like thereof. Additionally or alternatively, failure event may include any failure event as described in U.S. Nonprovisional application Ser. No. 17/113,647, filed on Dec. 7, 2020, and entitled “IN-FLIGHT STABILIZATION OF AN AIRCAFT,” the entirety of which is incorporated herein by reference. Flight controller 124 may efficaciously include any flight controllers as disclosed in U.S. Nonprovisional application. Ser. Nos. 17/222,539 and 17/113,647.

With continued reference to FIG. 2, flight controller 124 may include one or more computing devices. Computing device may include any computing device as described in this disclosure. Flight controller 124 may be onboard aircraft 200 and/or flight controller 124 may be remote from aircraft 200, as long as, in some embodiments, flight controller 124 is communicatively connected to aircraft 200. As used in this disclosure, “remote” is a spatial separation between two or more elements, systems, components or devices. Stated differently, two elements may be remote from one another if they are physically spaced apart. In an embodiment, flight controller 124 may include a proportional-integral-derivative (PID) controller.

Now referring to FIG. 3, an exemplary embodiment 300 of a flight controller 304 is illustrated. (Flight controller 124 of FIG. 1A and FIG. 2 may be the same as or similar to flight controller 304.) As used in this disclosure a “flight controller” is a computing device of a plurality of computing devices dedicated to data storage, security, distribution of traffic for load balancing, and flight instruction. Flight controller 304 may include and/or communicate with any computing device as described in this disclosure, including without limitation a microcontroller, microprocessor, digital signal processor (DSP) and/or system on a chip (SoC) as described in this disclosure. Further, flight controller 304 may include a single computing device operating independently, or may include two or more computing device operating in concert, in parallel, sequentially or the like; two or more computing devices may be included together in a single computing device or in two or more computing devices. In embodiments, flight controller 304 may be installed in an aircraft, may control the aircraft remotely, and/or may include an element installed in the aircraft and a remote element in communication therewith.

In an embodiment, and still referring to FIG. 3, flight controller 304 may include a signal transformation component 308. As used in this disclosure a “signal transformation component” is a component that transforms and/or converts a first signal to a second signal, wherein a signal may include one or more digital and/or analog signals. For example, and without limitation, signal transformation component 308 may be configured to perform one or more operations such as preprocessing, lexical analysis, parsing, semantic analysis, and the like thereof. In an embodiment, and without limitation, signal transformation component 308 may include one or more analog-to-digital convertors that transform a first signal of an analog signal to a second signal of a digital signal. For example, and without limitation, an analog-to-digital converter may convert an analog input signal to a 10-bit binary digital representation of that signal. In another embodiment, signal transformation component 308 may include transforming one or more low-level languages such as, but not limited to, machine languages and/or assembly languages. For example, and without limitation, signal transformation component 308 may include transforming a binary language signal to an assembly language signal. In an embodiment, and without limitation, signal transformation component 308 may include transforming one or more high-level languages and/or formal languages such as but not limited to alphabets, strings, and/or languages. For example, and without limitation, high-level languages may include one or more system languages, scripting languages, domain-specific languages, visual languages, esoteric languages, and the like thereof. As a further non-limiting example, high-level languages may include one or more algebraic formula languages, business data languages, string and list languages, object-oriented languages, and the like thereof.

Still referring to FIG. 3, signal transformation component 308 may be configured to optimize an intermediate representation 312. As used in this disclosure an “intermediate representation” is a data structure and/or code that represents the input signal. Signal transformation component 308 may optimize intermediate representation as a function of a data-flow analysis, dependence analysis, alias analysis, pointer analysis, escape analysis, and the like thereof. In an embodiment, and without limitation, signal transformation component 308 may optimize intermediate representation 312 as a function of one or more inline expansions, dead code eliminations, constant propagation, loop transformations, and/or automatic parallelization functions. In another embodiment, signal transformation component 308 may optimize intermediate representation as a function of a machine dependent optimization such as a peephole optimization, wherein a peephole optimization may rewrite short sequences of code into more efficient sequences of code. Signal transformation component 308 may optimize intermediate representation to generate an output language, wherein an “output language,” as used herein, is the native machine language of flight controller 304. For example, and without limitation, native machine language may include one or more binary and/or numerical languages.

In an embodiment, and without limitation, signal transformation component 308 may include transform one or more inputs and outputs as a function of an error correction code. An error correction code, also known as error correcting code (ECC), is an encoding of a message or lot of data using redundant information, permitting recovery of corrupted data. An ECC may include a block code, in which information is encoded on fixed-size packets and/or blocks of data elements such as symbols of predetermined size, bits, or the like. Reed-Solomon coding, in which message symbols within a symbol set having q symbols are encoded as coefficients of a polynomial of degree less than or equal to a natural number k, over a finite field F with q elements; strings so encoded have a minimum hamming distance of k+1, and permit correction of (q−k−1)/2 erroneous symbols. Block code may alternatively or additionally be implemented using Golay coding, also known as binary Golay coding, Bose-Chaudhuri, Hocquenghuem (BCH) coding, multidimensional parity-check coding, and/or Hamming codes. An ECC may alternatively or additionally be based on a convolutional code.

In an embodiment, and still referring to FIG. 3, flight controller 304 may include a reconfigurable hardware platform 316. A “reconfigurable hardware platform,” as used herein, is a component and/or unit of hardware that may be reprogrammed, such that, for instance, a data path between elements such as logic gates or other digital circuit elements may be modified to change an algorithm, state, logical sequence, or the like of the component and/or unit. This may be accomplished with such flexible high-speed computing fabrics as field-programmable gate arrays (FPGAs), which may include a grid of interconnected logic gates, connections between which may be severed and/or restored to program in modified logic. Reconfigurable hardware platform 316 may be reconfigured to enact any algorithm and/or algorithm selection process received from another computing device and/or created using machine-learning processes.

Still referring to FIG. 3, reconfigurable hardware platform 316 may include a logic component 320. As used in this disclosure a “logic component” is a component that executes instructions on output language. For example, and without limitation, logic component may perform basic arithmetic, logic, controlling, input/output operations, and the like thereof. Logic component 320 may include any suitable processor, such as without limitation a component incorporating logical circuitry for performing arithmetic and logical operations, such as an arithmetic and logic unit (ALU), which may be regulated with a state machine and directed by operational inputs from memory and/or sensors; logic component 320 may be organized according to Von Neumann and/or Harvard architecture as a non-limiting example. Logic component 320 may include, incorporate, and/or be incorporated in, without limitation, a microcontroller, microprocessor, digital signal processor (DSP), Field Programmable Gate Array (FPGA), Complex Programmable Logic Device (CPLD), Graphical Processing Unit (GPU), general purpose GPU, Tensor Processing Unit (TPU), analog or mixed signal processor, Trusted Platform Module (TPM), a floating point unit (FPU), and/or system on a chip (SoC). In an embodiment, logic component 320 may include one or more integrated circuit microprocessors, which may contain one or more central processing units, central processors, and/or main processors, on a single metal-oxide-semiconductor chip. Logic component 320 may be configured to execute a sequence of stored instructions to be performed on the output language and/or intermediate representation 312. Logic component 320 may be configured to fetch and/or retrieve the instruction from a memory cache, wherein a “memory cache,” as used in this disclosure, is a stored instruction set on flight controller 304. Logic component 320 may be configured to decode the instruction retrieved from the memory cache to opcodes and/or operands. Logic component 320 may be configured to execute the instruction on intermediate representation 312 and/or output language. For example, and without limitation, logic component 320 may be configured to execute an addition operation on intermediate representation 312 and/or output language.

In an embodiment, and without limitation, logic component 320 may be configured to calculate a flight element 324. As used in this disclosure a “flight element” is an element of datum denoting a relative status of aircraft. For example, and without limitation, flight element 324 may denote one or more torques, thrusts, airspeed velocities, forces, altitudes, groundspeed velocities, directions during flight, directions facing, forces, orientations, and the like thereof. For example, and without limitation, flight element 324 may denote that aircraft is cruising at an altitude and/or with a sufficient magnitude of forward thrust. As a further non-limiting example, flight status may denote that is building thrust and/or groundspeed velocity in preparation for a takeoff. As a further non-limiting example, flight element 324 may denote that aircraft is following a flight path accurately and/or sufficiently.

Still referring to FIG. 3, flight controller 304 may include a chipset component 328. As used in this disclosure a “chipset component” is a component that manages data flow. In an embodiment, and without limitation, chipset component 328 may include a northbridge data flow path, wherein the northbridge dataflow path may manage data flow from logic component 320 to a high-speed device and/or component, such as a RAM, graphics controller, and the like thereof. In another embodiment, and without limitation, chipset component 328 may include a southbridge data flow path, wherein the southbridge dataflow path may manage data flow from logic component 320 to lower-speed peripheral buses, such as a peripheral component interconnect (PCI), industry standard architecture (ICA), and the like thereof. In an embodiment, and without limitation, southbridge data flow path may include managing data flow between peripheral connections such as ethernet, USB, audio devices, and the like thereof. Additionally or alternatively, chipset component 328 may manage data flow between logic component 320, memory cache, and a flight component 208. As used in this disclosure (and with particular reference to FIG. 3) a “flight component” is a portion of an aircraft that can be moved or adjusted to affect one or more flight elements. For example, flight component 208 may include a component used to affect the aircrafts' roll and pitch which may comprise one or more ailerons. As a further example, flight component 208 may include a rudder to control yaw of an aircraft. In an embodiment, chipset component 328 may be configured to communicate with a plurality of flight components as a function of flight element 324. For example, and without limitation, chipset component 328 may transmit to an aircraft rotor to reduce torque of a first lift propulsor and increase the forward thrust produced by a pusher component to perform a flight maneuver.

In an embodiment, and still referring to FIG. 3, flight controller 304 may be configured generate an autonomous function. As used in this disclosure an “autonomous function” is a mode and/or function of flight controller 304 that controls aircraft automatically. For example, and without limitation, autonomous function may perform one or more aircraft maneuvers, take offs, landings, altitude adjustments, flight leveling adjustments, turns, climbs, and/or descents. As a further non-limiting example, autonomous function may adjust one or more airspeed velocities, thrusts, torques, and/or groundspeed velocities. As a further non-limiting example, autonomous function may perform one or more flight path corrections and/or flight path modifications as a function of flight element 324. In an embodiment, autonomous function may include one or more modes of autonomy such as, but not limited to, autonomous mode, semi-autonomous mode, and/or non-autonomous mode. As used in this disclosure “autonomous mode” is a mode that automatically adjusts and/or controls aircraft and/or the maneuvers of aircraft in its entirety. For example, autonomous mode may denote that flight controller 304 will adjust the aircraft. As used in this disclosure a “semi-autonomous mode” is a mode that automatically adjusts and/or controls a portion and/or section of aircraft. For example, and without limitation, semi-autonomous mode may denote that a pilot will control the propulsors, wherein flight controller 304 will control the ailerons and/or rudders. As used in this disclosure “non-autonomous mode” is a mode that denotes a pilot will control aircraft and/or maneuvers of aircraft in its entirety.

In an embodiment, and still referring to FIG. 3, flight controller 304 may generate autonomous function as a function of an autonomous machine-learning model. As used in this disclosure an “autonomous machine-learning model” is a machine-learning model to produce an autonomous function output given flight element 324 and a pilot signal 336 as inputs; this is in contrast to a non-machine learning software program where the commands to be executed are determined in advance by a user and written in a programming language. As used in this disclosure a “pilot signal” is an element of datum representing one or more functions a pilot is controlling and/or adjusting. For example, pilot signal 336 may denote that a pilot is controlling and/or maneuvering ailerons, wherein the pilot is not in control of the rudders and/or propulsors. In an embodiment, pilot signal 336 may include an implicit signal and/or an explicit signal. For example, and without limitation, pilot signal 336 may include an explicit signal, wherein the pilot explicitly states there is a lack of control and/or desire for autonomous function. As a further non-limiting example, pilot signal 336 may include an explicit signal directing flight controller 304 to control and/or maintain a portion of aircraft, a portion of the flight plan, the entire aircraft, and/or the entire flight plan. As a further non-limiting example, pilot signal 336 may include an implicit signal, wherein flight controller 304 detects a lack of control such as by a malfunction, torque alteration, flight path deviation, and the like thereof. In an embodiment, and without limitation, pilot signal 336 may include one or more explicit signals to reduce torque, and/or one or more implicit signals that torque may be reduced due to reduction of airspeed velocity. In an embodiment, and without limitation, pilot signal 336 may include one or more local and/or global signals. For example, and without limitation, pilot signal 336 may include a local signal that is transmitted by a pilot and/or crew member. As a further non-limiting example, pilot signal 336 may include a global signal that is transmitted by air traffic control and/or one or more remote users that are in communication with the pilot of aircraft. In an embodiment, pilot signal 336 may be received as a function of a tri-state bus and/or multiplexor that denotes an explicit pilot signal should be transmitted prior to any implicit or global pilot signal.

Still referring to FIG. 3, autonomous machine-learning model may include one or more autonomous machine-learning processes such as supervised, unsupervised, or reinforcement machine-learning processes that flight controller 304 and/or a remote device may or may not use in the generation of autonomous function. As used in this disclosure “remote device” is an external device to flight controller 304. Additionally or alternatively, autonomous machine-learning model may include one or more autonomous machine-learning processes that a field-programmable gate array (FPGA) may or may not use in the generation of autonomous function. Autonomous machine-learning process may include, without limitation machine learning processes such as simple linear regression, multiple linear regression, polynomial regression, support vector regression, ridge regression, lasso regression, elasticnet regression, decision tree regression, random forest regression, logistic regression, logistic classification, K-nearest neighbors, support vector machines, kernel support vector machines, naïve bayes, decision tree classification, random forest classification, K-means clustering, hierarchical clustering, dimensionality reduction, principal component analysis, linear discriminant analysis, kernel principal component analysis, Q-learning, State Action Reward State Action (SARSA), Deep-Q network, Markov decision processes, Deep Deterministic Policy Gradient (DDPG), or the like thereof.

In an embodiment, and still referring to FIG. 3, autonomous machine learning model may be trained as a function of autonomous training data, wherein autonomous training data may correlate a flight element, pilot signal, and/or simulation data to an autonomous function. For example, and without limitation, a flight element of an airspeed velocity, a pilot signal of limited and/or no control of propulsors, and a simulation data of required airspeed velocity to reach the destination may result in an autonomous function that includes a semi-autonomous mode to increase thrust of the propulsors. Autonomous training data may be received as a function of user-entered valuations of flight elements, pilot signals, simulation data, and/or autonomous functions. Flight controller 304 may receive autonomous training data by receiving correlations of flight element, pilot signal, and/or simulation data to an autonomous function that were previously received and/or determined during a previous iteration of generation of autonomous function. Autonomous training data may be received by one or more remote devices and/or FPGAs that at least correlate a flight element, pilot signal, and/or simulation data to an autonomous function. Autonomous training data may be received in the form of one or more user-entered correlations of a flight element, pilot signal, and/or simulation data to an autonomous function.

Still referring to FIG. 3, flight controller 304 may receive autonomous machine-learning model from a remote device and/or FPGA that utilizes one or more autonomous machine learning processes, wherein a remote device and an FPGA is described above in detail. For example, and without limitation, a remote device may include a computing device, external device, processor, FPGA, microprocessor and the like thereof. Remote device and/or FPGA may perform the autonomous machine-learning process using autonomous training data to generate autonomous function and transmit the output to flight controller 304. Remote device and/or FPGA may transmit a signal, bit, datum, or parameter to flight controller 304 that at least relates to autonomous function. Additionally or alternatively, the remote device and/or FPGA may provide an updated machine-learning model. For example, and without limitation, an updated machine-learning model may be comprised of a firmware update, a software update, an autonomous machine-learning process correction, and the like thereof. As a non-limiting example a software update may incorporate a new simulation data that relates to a modified flight element. Additionally or alternatively, the updated machine learning model may be transmitted to the remote device and/or FPGA, wherein the remote device and/or FPGA may replace the autonomous machine-learning model with the updated machine-learning model and generate the autonomous function as a function of the flight element, pilot signal, and/or simulation data using the updated machine-learning model. The updated machine-learning model may be transmitted by the remote device and/or FPGA and received by flight controller 304 as a software update, firmware update, or corrected autonomous machine-learning model. For example, and without limitation autonomous machine learning model may utilize a neural net machine-learning process, wherein the updated machine-learning model may incorporate a gradient boosting machine-learning process.

Still referring to FIG. 3, flight controller 304 may include, be included in, and/or communicate with a mobile device such as a mobile telephone or smartphone. Further, flight controller may communicate with one or more additional devices as described below in further detail via a network interface device. The network interface device may be utilized for commutatively connecting a flight controller to one or more of a variety of networks, and one or more devices. Examples of a network interface device include, but are not limited to, a network interface card (e.g., a mobile network interface card, a LAN card), a modem, and any combination thereof. Examples of a network include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a data network associated with a telephone/voice provider (e.g., a mobile communications provider data and/or voice network), a direct connection between two computing devices, and any combinations thereof. The network may include any network topology and can may employ a wired and/or a wireless mode of communication.

In an embodiment, and still referring to FIG. 3, flight controller 304 may include, but is not limited to, for example, a cluster of flight controllers in a first location and a second flight controller or cluster of flight controllers in a second location. Flight controller 304 may include one or more flight controllers dedicated to data storage, security, distribution of traffic for load balancing, and the like. Flight controller 304 may be configured to distribute one or more computing tasks as described below across a plurality of flight controllers, which may operate in parallel, in series, redundantly, or in any other manner used for distribution of tasks or memory between computing devices. For example, and without limitation, flight controller 304 may implement a control algorithm to distribute and/or command the plurality of flight controllers. As used in this disclosure a “control algorithm” is a finite sequence of well-defined computer implementable instructions that may determine the flight component of the plurality of flight components to be adjusted. For example, and without limitation, control algorithm may include one or more algorithms that reduce and/or prevent aviation asymmetry. As a further non-limiting example, control algorithms may include one or more models generated as a function of a software including, but not limited to Simulink by MathWorks, Natick, Mass., USA. In an embodiment, and without limitation, control algorithm may be configured to generate an auto-code, wherein an “auto-code,” is used herein, is a code and/or algorithm that is generated as a function of the one or more models and/or software's. In another embodiment, control algorithm may be configured to produce a segmented control algorithm. As used in this disclosure a “segmented control algorithm” is control algorithm that has been separated and/or parsed into discrete sections. For example, and without limitation, segmented control algorithm may parse control algorithm into two or more segments, wherein each segment of control algorithm may be performed by one or more flight controllers operating on distinct flight components.

In an embodiment, and still referring to FIG. 3, control algorithm may be configured to determine a segmentation boundary as a function of segmented control algorithm. As used in this disclosure a “segmentation boundary” is a limit and/or delineation associated with the segments of the segmented control algorithm. For example, and without limitation, segmentation boundary may denote that a segment in the control algorithm has a first starting section and/or a first ending section. As a further non-limiting example, segmentation boundary may include one or more boundaries associated with an ability of flight component 208. In an embodiment, control algorithm may be configured to create an optimized signal communication as a function of segmentation boundary. For example, and without limitation, optimized signal communication may include identifying the discrete timing required to transmit and/or receive the one or more segmentation boundaries. In an embodiment, and without limitation, creating optimized signal communication further comprises separating a plurality of signal codes across the plurality of flight controllers. For example, and without limitation the plurality of flight controllers may include one or more formal networks, wherein formal networks transmit data along an authority chain and/or are limited to task-related communications. As a further non-limiting example, communication network may include informal networks, wherein informal networks transmit data in any direction. In an embodiment, and without limitation, the plurality of flight controllers may include a chain path, wherein a “chain path,” as used herein, is a linear communication path comprising a hierarchy that data may flow through. In an embodiment, and without limitation, the plurality of flight controllers may include an all-channel path, wherein an “all-channel path,” as used herein, is a communication path that is not restricted to a particular direction. For example, and without limitation, data may be transmitted upward, downward, laterally, and the like thereof. In an embodiment, and without limitation, the plurality of flight controllers may include one or more neural networks that assign a weighted value to a transmitted datum. For example, and without limitation, a weighted value may be assigned as a function of one or more signals denoting that a flight component is malfunctioning and/or in a failure state.

Still referring to FIG. 3, the plurality of flight controllers may include a master bus controller. As used in this disclosure a “master bus controller” is one or more devices and/or components that are connected to a bus to initiate a direct memory access transaction, wherein a bus is one or more terminals in a bus architecture. Master bus controller may communicate using synchronous and/or asynchronous bus control protocols. In an embodiment, master bus controller may include flight controller 304. In another embodiment, master bus controller may include one or more universal asynchronous receiver-transmitters (UART). For example, and without limitation, master bus controller may include one or more bus architectures that allow a bus to initiate a direct memory access transaction from one or more buses in the bus architectures. As a further non-limiting example, master bus controller may include one or more peripheral devices and/or components to communicate with another peripheral device and/or component and/or the master bus controller. In an embodiment, master bus controller may be configured to perform bus arbitration. As used in this disclosure “bus arbitration” is method and/or scheme to prevent multiple buses from attempting to communicate with and/or connect to master bus controller. For example and without limitation, bus arbitration may include one or more schemes such as a small computer interface system, wherein a small computer interface system is a set of standards for physical connecting and transferring data between peripheral devices and master bus controller by defining commands, protocols, electrical, optical, and/or logical interfaces. In an embodiment, master bus controller may receive intermediate representation 312 and/or output language from logic component 320, wherein output language may include one or more analog-to-digital conversions, low bit rate transmissions, message encryptions, digital signals, binary signals, logic signals, analog signals, and the like thereof described above in detail.

Still referring to FIG. 3, master bus controller may communicate with a slave bus. As used in this disclosure a “slave bus” is one or more peripheral devices and/or components that initiate a bus transfer. For example, and without limitation, slave bus may receive one or more controls and/or asymmetric communications from master bus controller, wherein slave bus transfers data stored to master bus controller. In an embodiment, and without limitation, slave bus may include one or more internal buses, such as but not limited to a/an internal data bus, memory bus, system bus, front-side bus, and the like thereof. In another embodiment, and without limitation, slave bus may include one or more external buses such as external flight controllers, external computers, remote devices, printers, aircraft computer systems, flight control systems, and the like thereof.

In an embodiment, and still referring to FIG. 3, control algorithm may optimize signal communication as a function of determining one or more discrete timings. For example, and without limitation master bus controller may synchronize timing of the segmented control algorithm by injecting high priority timing signals on a bus of the master bus control. As used in this disclosure a “high priority timing signal” is information denoting that the information is important. For example, and without limitation, high priority timing signal may denote that a section of control algorithm is of high priority and should be analyzed and/or transmitted prior to any other sections being analyzed and/or transmitted. In an embodiment, high priority timing signal may include one or more priority packets. As used in this disclosure a “priority packet” is a formatted unit of data that is communicated between the plurality of flight controllers. For example, and without limitation, priority packet may denote that a section of control algorithm should be used and/or is of greater priority than other sections.

Still referring to FIG. 3, flight controller 304 may also be implemented using a “shared nothing” architecture in which data is cached at the worker, in an embodiment, this may enable scalability of aircraft and/or computing device. Flight controller 304 may include a distributer flight controller. As used in this disclosure a “distributer flight controller” is a component that adjusts and/or controls a plurality of flight components as a function of a plurality of flight controllers. For example, distributer flight controller may include a flight controller that communicates with a plurality of additional flight controllers and/or clusters of flight controllers. In an embodiment, distributed flight control may include one or more neural networks. For example, neural network also known as an artificial neural network, is a network of “nodes,” or data structures having one or more inputs, one or more outputs, and a function determining outputs based on inputs. Such nodes may be organized in a network, such as without limitation a convolutional neural network, including an input layer of nodes, one or more intermediate layers, and an output layer of nodes. Connections between nodes may be created via the process of “training” the network, in which elements from a training dataset are applied to the input nodes, a suitable training algorithm (such as Levenberg-Marquardt, conjugate gradient, simulated annealing, or other algorithms) is then used to adjust the connections and weights between nodes in adjacent layers of the neural network to produce the desired values at the output nodes. This process is sometimes referred to as deep learning.

Still referring to FIG. 3, a node may include, without limitation a plurality of inputs x_(i) that may receive numerical values from inputs to a neural network containing the node and/or from other nodes. Node may perform a weighted sum of inputs using weights w_(i) that are multiplied by respective inputs x_(i). Additionally or alternatively, a bias b may be added to the weighted sum of the inputs such that an offset is added to each unit in the neural network layer that is independent of the input to the layer. The weighted sum may then be input into a function φ, which may generate one or more outputs y. Weight w_(i) applied to an input x_(i) may indicate whether the input is “excitatory,” indicating that it has strong influence on the one or more outputs y, for instance by the corresponding weight having a large numerical value, and/or a “inhibitory,” indicating it has a weak effect influence on the one more inputs y, for instance by the corresponding weight having a small numerical value. The values of weights w_(i) may be determined by training a neural network using training data, which may be performed using any suitable process as described above. In an embodiment, and without limitation, a neural network may receive semantic units as inputs and output vectors representing such semantic units according to weights w_(i) that are derived using machine-learning processes as described in this disclosure.

Still referring to FIG. 3, flight controller may include a sub-controller 340. As used in this disclosure a “sub-controller” is a controller and/or component that is part of a distributed controller as described above; for instance, flight controller 304 may be and/or include a distributed flight controller made up of one or more sub-controllers. For example, and without limitation, sub-controller 340 may include any controllers and/or components thereof that are similar to distributed flight controller and/or flight controller as described above. Sub-controller 340 may include any component of any flight controller as described above. Sub-controller 340 may be implemented in any manner suitable for implementation of a flight controller as described above. As a further non-limiting example, sub-controller 340 may include one or more processors, logic components and/or computing devices capable of receiving, processing, and/or transmitting data across the distributed flight controller as described above. As a further non-limiting example, sub-controller 340 may include a controller that receives a signal from a first flight controller and/or first distributed flight controller component and transmits the signal to a plurality of additional sub-controllers and/or flight components.

Still referring to FIG. 3, flight controller may include a co-controller 344. As used in this disclosure a “co-controller” is a controller and/or component that joins flight controller 304 as components and/or nodes of a distributer flight controller as described above. For example, and without limitation, co-controller 344 may include one or more controllers and/or components that are similar to flight controller 304. As a further non-limiting example, co-controller 344 may include any controller and/or component that joins flight controller 304 to distributer flight controller. As a further non-limiting example, co-controller 344 may include one or more processors, logic components and/or computing devices capable of receiving, processing, and/or transmitting data to and/or from flight controller 304 to distributed flight control system. Co-controller 344 may include any component of any flight controller as described above. Co-controller 344 may be implemented in any manner suitable for implementation of a flight controller as described above.

In an embodiment, and with continued reference to FIG. 3, flight controller 304 may be designed and/or configured to perform any method, method step, or sequence of method steps in any embodiment described in this disclosure, in any order and with any degree of repetition. For instance, flight controller 304 may be configured to perform a single step or sequence repeatedly until a desired or commanded outcome is achieved; repetition of a step or a sequence of steps may be performed iteratively and/or recursively using outputs of previous repetitions as inputs to subsequent repetitions, aggregating inputs and/or outputs of repetitions to produce an aggregate result, reduction or decrement of one or more variables such as global variables, and/or division of a larger processing task into a set of iteratively addressed smaller processing tasks. Flight controller may perform any step or sequence of steps as described in this disclosure in parallel, such as simultaneously and/or substantially simultaneously performing a step two or more times using two or more parallel threads, processor cores, or the like; division of tasks between parallel threads and/or processes may be performed according to any protocol suitable for division of tasks between iterations. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various ways in which steps, sequences of steps, processing tasks, and/or data may be subdivided, shared, or otherwise dealt with using iteration, recursion, and/or parallel processing.

Referring now to FIG. 4, an exemplary embodiment of a machine-learning module 400 that may perform one or more machine-learning processes as described in this disclosure is illustrated. Machine-learning module may perform determinations, classification, and/or analysis steps, methods, processes, or the like as described in this disclosure using machine learning processes. A “machine learning process,” as used in this disclosure, is a process that automatedly uses training data 404 to generate an algorithm that will be performed by a computing device/module to produce outputs 408 given data provided as inputs 412; this is in contrast to a non-machine learning software program where the commands to be executed are determined in advance by a user and written in a programming language.

Still referring to FIG. 4, “training data,” as used herein, is data containing correlations that a machine-learning process may use to model relationships between two or more categories of data elements. For instance, and without limitation, training data 404 may include a plurality of data entries, each entry representing a set of data elements that were recorded, received, and/or generated together; data elements may be correlated by shared existence in a given data entry, by proximity in a given data entry, or the like. Multiple data entries in training data 404 may evince one or more trends in correlations between categories of data elements; for instance, and without limitation, a higher value of a first data element belonging to a first category of data element may tend to correlate to a higher value of a second data element belonging to a second category of data element, indicating a possible proportional or other mathematical relationship linking values belonging to the two categories. Multiple categories of data elements may be related in training data 404 according to various correlations; correlations may indicate causative and/or predictive links between categories of data elements, which may be modeled as relationships such as mathematical relationships by machine-learning processes as described in further detail below. Training data 404 may be formatted and/or organized by categories of data elements, for instance by associating data elements with one or more descriptors corresponding to categories of data elements. As a non-limiting example, training data 404 may include data entered in standardized forms by persons or processes, such that entry of a given data element in a given field in a form may be mapped to one or more descriptors of categories. Elements in training data 404 may be linked to descriptors of categories by tags, tokens, or other data elements; for instance, and without limitation, training data 404 may be provided in fixed-length formats, formats linking positions of data to categories such as comma-separated value (CSV) formats and/or self-describing formats such as extensible markup language (XML), JavaScript Object Notation (JSON), or the like, enabling processes or devices to detect categories of data.

Alternatively or additionally, and continuing to refer to FIG. 4, training data 404 may include one or more elements that are not categorized; that is, training data 404 may not be formatted or contain descriptors for some elements of data. Machine-learning algorithms and/or other processes may sort training data 404 according to one or more categorizations using, for instance, natural language processing algorithms, tokenization, detection of correlated values in raw data and the like; categories may be generated using correlation and/or other processing algorithms. As a non-limiting example, in a corpus of text, phrases making up a number “n” of compound words, such as nouns modified by other nouns, may be identified according to a statistically significant prevalence of n-grams containing such words in a particular order; such an n-gram may be categorized as an element of language such as a “word” to be tracked similarly to single words, generating a new category as a result of statistical analysis. Similarly, in a data entry including some textual data, a person's name may be identified by reference to a list, dictionary, or other compendium of terms, permitting ad-hoc categorization by machine-learning algorithms, and/or automated association of data in the data entry with descriptors or into a given format. The ability to categorize data entries automatedly may enable the same training data 404 to be made applicable for two or more distinct machine-learning algorithms as described in further detail below. Training data 404 used by machine-learning module 400 may correlate any input data as described in this disclosure to any output data as described in this disclosure. As a non-limiting illustrative example flight elements and/or pilot signals may be inputs, wherein an output may be an autonomous function.

Further referring to FIG. 4, training data may be filtered, sorted, and/or selected using one or more supervised and/or unsupervised machine-learning processes and/or models as described in further detail below; such models may include without limitation a training data classifier 416. Training data classifier 416 may include a “classifier,” which as used in this disclosure is a machine-learning model as defined below, such as a mathematical model, neural net, or program generated by a machine learning algorithm known as a “classification algorithm,” as described in further detail below, that sorts inputs into categories or bins of data, outputting the categories or bins of data and/or labels associated therewith. A classifier may be configured to output at least a datum that labels or otherwise identifies a set of data that are clustered together, found to be close under a distance metric as described below, or the like. Machine-learning module 400 may generate a classifier using a classification algorithm, defined as a processes whereby a computing device and/or any module and/or component operating thereon derives a classifier from training data 404. Classification may be performed using, without limitation, linear classifiers such as without limitation logistic regression and/or naive Bayes classifiers, nearest neighbor classifiers such as k-nearest neighbors classifiers, support vector machines, least squares support vector machines, fisher's linear discriminant, quadratic classifiers, decision trees, boosted trees, random forest classifiers, learning vector quantization, and/or neural network-based classifiers. As a non-limiting example, training data classifier 416 may classify elements of training data to sub-categories of flight elements such as torques, forces, thrusts, directions, and the like thereof.

Still referring to FIG. 4, machine-learning module 400 may be configured to perform a lazy-learning process 420 and/or protocol, which may alternatively be referred to as a “lazy loading” or “call-when-needed” process and/or protocol, may be a process whereby machine learning is conducted upon receipt of an input to be converted to an output, by combining the input and training set to derive the algorithm to be used to produce the output on demand. For instance, an initial set of simulations may be performed to cover an initial heuristic and/or “first guess” at an output and/or relationship. As a non-limiting example, an initial heuristic may include a ranking of associations between inputs and elements of training data 404. Heuristic may include selecting some number of highest-ranking associations and/or training data 404 elements. Lazy learning may implement any suitable lazy learning algorithm, including without limitation a K-nearest neighbors algorithm, a lazy naïve Bayes algorithm, or the like; persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various lazy-learning algorithms that may be applied to generate outputs as described in this disclosure, including without limitation lazy learning applications of machine-learning algorithms as described in further detail below.

Alternatively or additionally, and with continued reference to FIG. 4, machine-learning processes as described in this disclosure may be used to generate machine-learning models 424. A “machine-learning model,” as used in this disclosure, is a mathematical and/or algorithmic representation of a relationship between inputs and outputs, as generated using any machine-learning process including without limitation any process as described above, and stored in memory; an input is submitted to a machine-learning model 424 once created, which generates an output based on the relationship that was derived. For instance, and without limitation, a linear regression model, generated using a linear regression algorithm, may compute a linear combination of input data using coefficients derived during machine-learning processes to calculate an output datum. As a further non-limiting example, a machine-learning model 424 may be generated by creating an artificial neural network, such as a convolutional neural network comprising an input layer of nodes, one or more intermediate layers, and an output layer of nodes. Connections between nodes may be created via the process of “training” the network, in which elements from a training data 404 set are applied to the input nodes, a suitable training algorithm (such as Levenberg-Marquardt, conjugate gradient, simulated annealing, or other algorithms) is then used to adjust the connections and weights between nodes in adjacent layers of the neural network to produce the desired values at the output nodes. This process is sometimes referred to as deep learning.

Still referring to FIG. 4, machine-learning algorithms may include at least a supervised machine-learning process 428. At least a supervised machine-learning process 428, as defined herein, include algorithms that receive a training set relating a number of inputs to a number of outputs, and seek to find one or more mathematical relations relating inputs to outputs, where each of the one or more mathematical relations is optimal according to some criterion specified to the algorithm using some scoring function. For instance, a supervised learning algorithm may include flight elements and/or pilot signals as described above as inputs, autonomous functions as outputs, and a scoring function representing a desired form of relationship to be detected between inputs and outputs; scoring function may, for instance, seek to maximize the probability that a given input and/or combination of elements inputs is associated with a given output to minimize the probability that a given input is not associated with a given output. Scoring function may be expressed as a risk function representing an “expected loss” of an algorithm relating inputs to outputs, where loss is computed as an error function representing a degree to which a prediction generated by the relation is incorrect when compared to a given input-output pair provided in training data 404. Persons skilled in the art, upon reviewing the entirety of this disclosure, will be aware of various possible variations of at least a supervised machine-learning process 428 that may be used to determine relation between inputs and outputs. Supervised machine-learning processes may include classification algorithms as defined above.

Further referring to FIG. 4, machine learning processes may include at least an unsupervised machine-learning processes 432. An unsupervised machine-learning process, as used herein, is a process that derives inferences in datasets without regard to labels; as a result, an unsupervised machine-learning process may be free to discover any structure, relationship, and/or correlation provided in the data. Unsupervised processes may not require a response variable; unsupervised processes may be used to find interesting patterns and/or inferences between variables, to determine a degree of correlation between two or more variables, or the like.

Still referring to FIG. 4, machine-learning module 400 may be designed and configured to create a machine-learning model 424 using techniques for development of linear regression models. Linear regression models may include ordinary least squares regression, which aims to minimize the square of the difference between predicted outcomes and actual outcomes according to an appropriate norm for measuring such a difference (e.g. a vector-space distance norm); coefficients of the resulting linear equation may be modified to improve minimization. Linear regression models may include ridge regression methods, where the function to be minimized includes the least-squares function plus term multiplying the square of each coefficient by a scalar amount to penalize large coefficients. Linear regression models may include least absolute shrinkage and selection operator (LASSO) models, in which ridge regression is combined with multiplying the least-squares term by a factor of 1 divided by double the number of samples. Linear regression models may include a multi-task lasso model wherein the norm applied in the least-squares term of the lasso model is the Frobenius norm amounting to the square root of the sum of squares of all terms. Linear regression models may include the elastic net model, a multi-task elastic net model, a least angle regression model, a LARS lasso model, an orthogonal matching pursuit model, a Bayesian regression model, a logistic regression model, a stochastic gradient descent model, a perceptron model, a passive aggressive algorithm, a robustness regression model, a Huber regression model, or any other suitable model that may occur to persons skilled in the art upon reviewing the entirety of this disclosure. Linear regression models may be generalized in an embodiment to polynomial regression models, whereby a polynomial equation (e.g. a quadratic, cubic or higher-order equation) providing a best predicted output/actual output fit is sought; similar methods to those described above may be applied to minimize error functions, as will be apparent to persons skilled in the art upon reviewing the entirety of this disclosure.

Continuing to refer to FIG. 4, machine-learning algorithms may include, without limitation, linear discriminant analysis. Machine-learning algorithm may include quadratic discriminate analysis. Machine-learning algorithms may include kernel ridge regression. Machine-learning algorithms may include support vector machines, including without limitation support vector classification-based regression processes. Machine-learning algorithms may include stochastic gradient descent algorithms, including classification and regression algorithms based on stochastic gradient descent. Machine-learning algorithms may include nearest neighbors algorithms. Machine-learning algorithms may include Gaussian processes such as Gaussian Process Regression. Machine-learning algorithms may include cross-decomposition algorithms, including partial least squares and/or canonical correlation analysis. Machine-learning algorithms may include naïve Bayes methods. Machine-learning algorithms may include algorithms based on decision trees, such as decision tree classification or regression algorithms. Machine-learning algorithms may include ensemble methods such as bagging meta-estimator, forest of randomized tress, AdaBoost, gradient tree boosting, and/or voting classifier methods. Machine-learning algorithms may include neural net algorithms, including convolutional neural net processes.

Now referring to FIG. 5, an exemplary embodiment of a method 500 for authentication of an electric aircraft for recharging is illustrated. Electric aircraft may be any of the aircrafts as disclosed herein and described above with reference to at least FIG. 1A and FIG. 2. In an embodiment, electric aircraft may include an electric vertical takeoff and landing (eVTOL) aircraft.

Still referring to FIG. 5, at step 505, an authentication datum from an electric aircraft is received at a charging connector. Authentication datum may include any of the authentication datums as disclosed herein and described above with reference to at least FIG. 1A. Electric aircraft may include any of the electric aircrafts as disclosed herein and described above with reference to at least FIG. 1A and FIG. 2. Charging connector may include any of the charging connectors as disclosed herein and described above with reference to at least FIG. 1A. Charging connector is configured to mate with an electric aircraft port of electric aircraft. Electric aircraft port may include any of the electric aircraft ports as disclosed herein and described above with reference to at least FIG. 1A. Mating may be by any mating means as disclosed in the entirety of this disclosure.

Continuing to refer to FIG. 5, at step 510, authentication datum is verified at a computing device communicatively connected to charging connector. Computing device may include any of the computing devices as disclosed herein and described above with reference to at least FIG. 1A. Verification may be by any verification means as disclosed in the entirety of this disclosure.

With continued reference to FIG. 5, at step 515, charging (or recharging) of electric aircraft is enabled, at charging connector and by computing device, as a function of verification of authentication datum. Charging (or recharging) may be by any charging (or recharging) means as disclosed in the entirety of this disclosure. Enablement may be by any enabling means as disclosed in the entirety of this disclosure.

It is to be noted that any one or more of the aspects and embodiments described herein may be conveniently implemented using one or more machines (e.g., one or more computing devices that are utilized as a user computing device for an electronic document, one or more server devices, such as a document server, etc.) programmed according to the teachings of the present specification, as will be apparent to those of ordinary skill in the computer art. Appropriate software coding can readily be prepared by skilled programmers based on the teachings of the present disclosure, as will be apparent to those of ordinary skill in the software art. Aspects and implementations discussed above employing software and/or software modules may also include appropriate hardware for assisting in the implementation of the machine executable instructions of the software and/or software module.

Such software may be a computer program product that employs a machine-readable storage medium. A machine-readable storage medium may be any medium that is capable of storing and/or encoding a sequence of instructions for execution by a machine (e.g., a computing device) and that causes the machine to perform any one of the methodologies and/or embodiments described herein. Examples of a machine-readable storage medium include, but are not limited to, a magnetic disk, an optical disc (e.g., CD, CD-R, DVD, DVD-R, etc.), a magneto-optical disk, a read-only memory “ROM” device, a random access memory “RAM” device, a magnetic card, an optical card, a solid-state memory device, an EPROM, an EEPROM, and any combinations thereof. A machine-readable medium, as used herein, is intended to include a single medium as well as a collection of physically separate media, such as, for example, a collection of compact discs or one or more hard disk drives in combination with a computer memory. As used herein, a machine-readable storage medium does not include transitory forms of signal transmission.

Such software may also include information (e.g., data) carried as a data signal on a data carrier, such as a carrier wave. For example, machine-executable information may be included as a data-carrying signal embodied in a data carrier in which the signal encodes a sequence of instruction, or portion thereof, for execution by a machine (e.g., a computing device) and any related information (e.g., data structures and data) that causes the machine to perform any one of the methodologies and/or embodiments described herein.

Examples of a computing device include, but are not limited to, an electronic book reading device, a computer workstation, a terminal computer, a server computer, a handheld device (e.g., a tablet computer, a smartphone, etc.), a web appliance, a network router, a network switch, a network bridge, any machine capable of executing a sequence of instructions that specify an action to be taken by that machine, and any combinations thereof. In one example, a computing device may include and/or be included in a kiosk.

FIG. 6 shows a diagrammatic representation of one embodiment of a computing device in the exemplary form of a computer system 600 within which a set of instructions for causing a control system to perform any one or more of the aspects and/or methodologies of the present disclosure may be executed. It is also contemplated that multiple computing devices may be utilized to implement a specially configured set of instructions for causing one or more of the devices to perform any one or more of the aspects and/or methodologies of the present disclosure. Computer system 600 includes a processor 604 and a memory 608 that communicate with each other, and with other components, via a bus 612. Bus 612 may include any of several types of bus structures including, but not limited to, a memory bus, a memory controller, a peripheral bus, a local bus, and any combinations thereof, using any of a variety of bus architectures.

Processor 604 may include any suitable processor, such as without limitation a processor incorporating logical circuitry for performing arithmetic and logical operations, such as an arithmetic and logic unit (ALU), which may be regulated with a state machine and directed by operational inputs from memory and/or sensors; processor 604 may be organized according to Von Neumann and/or Harvard architecture as a non-limiting example. Processor 604 may include, incorporate, and/or be incorporated in, without limitation, a microcontroller, microprocessor, digital signal processor (DSP), Field Programmable Gate Array (FPGA), Complex Programmable Logic Device (CPLD), Graphical Processing Unit (GPU), general purpose GPU, Tensor Processing Unit (TPU), analog or mixed signal processor, Trusted Platform Module (TPM), a floating point unit (FPU), and/or system on a chip (SoC).

Memory 608 may include various components (e.g., machine-readable media) including, but not limited to, a random-access memory component, a read only component, and any combinations thereof. In one example, a basic input/output system 616 (BIOS), including basic routines that help to transfer information between elements within computer system 600, such as during start-up, may be stored in memory 608. Memory 608 may also include (e.g., stored on one or more machine-readable media) instructions (e.g., software) 620 embodying any one or more of the aspects and/or methodologies of the present disclosure. In another example, memory 608 may further include any number of program modules including, but not limited to, an operating system, one or more application programs, other program modules, program data, and any combinations thereof.

Computer system 600 may also include a storage device 624. Examples of a storage device (e.g., storage device 624) include, but are not limited to, a hard disk drive, a magnetic disk drive, an optical disc drive in combination with an optical medium, a solid-state memory device, and any combinations thereof. Storage device 624 may be connected to bus 612 by an appropriate interface (not shown). Example interfaces include, but are not limited to, SCSI, advanced technology attachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394 (FIREWIRE), and any combinations thereof. In one example, storage device 624 (or one or more components thereof) may be removably interfaced with computer system 600 (e.g., via an external port connector (not shown)). Particularly, storage device 624 and an associated machine-readable medium 628 may provide nonvolatile and/or volatile storage of machine-readable instructions, data structures, program modules, and/or other data for computer system 600. In one example, software 620 may reside, completely or partially, within machine-readable medium 628. In another example, software 620 may reside, completely or partially, within processor 604.

Computer system 600 may also include an input device 632. In one example, a user of computer system 600 may enter commands and/or other information into computer system 600 via input device 632. Examples of an input device 632 include, but are not limited to, an alpha-numeric input device (e.g., a keyboard), a pointing device, a joystick, a gamepad, an audio input device (e.g., a microphone, a voice response system, etc.), a cursor control device (e.g., a mouse), a touchpad, an optical scanner, a video capture device (e.g., a still camera, a video camera), a touchscreen, and any combinations thereof. Input device 632 may be interfaced to bus 612 via any of a variety of interfaces (not shown) including, but not limited to, a serial interface, a parallel interface, a game port, a USB interface, a FIREWIRE interface, a direct interface to bus 612, and any combinations thereof. Input device 632 may include a touch screen interface that may be a part of or separate from display 636, discussed further below. Input device 632 may be utilized as a user selection device for selecting one or more graphical representations in a graphical interface as described above.

A user may also input commands and/or other information to computer system 600 via storage device 624 (e.g., a removable disk drive, a flash drive, etc.) and/or network interface device 640. A network interface device, such as network interface device 640, may be utilized for connecting computer system 600 to one or more of a variety of networks, such as network 644, and one or more remote devices 648 connected thereto. Examples of a network interface device include, but are not limited to, a network interface card (e.g., a mobile network interface card, a LAN card), a modem, and any combination thereof. Examples of a network include, but are not limited to, a wide area network (e.g., the Internet, an enterprise network), a local area network (e.g., a network associated with an office, a building, a campus or other relatively small geographic space), a telephone network, a data network associated with a telephone/voice provider (e.g., a mobile communications provider data and/or voice network), a direct connection between two computing devices, and any combinations thereof. A network, such as network 644, may employ a wired and/or a wireless mode of communication. In general, any network topology may be used. Information (e.g., data, software 620, etc.) may be communicated to and/or from computer system 600 via network interface device 640.

Computer system 600 may further include a video display adapter 652 for communicating a displayable image to a display device, such as display device 636. Examples of a display device include, but are not limited to, a liquid crystal display (LCD), a cathode ray tube (CRT), a plasma display, a light emitting diode (LED) display, and any combinations thereof. Display adapter 652 and display device 636 may be utilized in combination with processor 604 to provide graphical representations of aspects of the present disclosure. In addition to a display device, computer system 600 may include one or more other peripheral output devices including, but not limited to, an audio speaker, a printer, and any combinations thereof. Such peripheral output devices may be connected to bus 612 via a peripheral interface 656. Examples of a peripheral interface include, but are not limited to, a serial port, a USB connection, a FIREWIRE connection, a parallel connection, and any combinations thereof.

The foregoing has been a detailed description of illustrative embodiments of the invention. Various modifications and additions can be made without departing from the spirit and scope of this invention. Features of each of the various embodiments described above may be combined with features of other described embodiments as appropriate in order to provide a multiplicity of feature combinations in associated new embodiments. Furthermore, while the foregoing describes a number of separate embodiments, what has been described herein is merely illustrative of the application of the principles of the present invention. Additionally, although particular methods herein may be illustrated and/or described as being performed in a specific order, the ordering is highly variable within ordinary skill to achieve methods and systems according to the present disclosure. Accordingly, this description is meant to be taken only by way of example, and not to otherwise limit the scope of this invention.

Exemplary embodiments have been disclosed above and illustrated in the accompanying drawings. It will be understood by those skilled in the art that various changes, omissions and additions may be made to that which is specifically disclosed herein without departing from the spirit and scope of the present invention. 

What is claimed is:
 1. A method for authentication of an electric aircraft for recharging, the method comprising: receiving, at a charging connector, an authentication datum from an electric aircraft, wherein the charging connector is configured to mate with an electric aircraft port of the electric aircraft; verifying, at a computing device communicatively connected to the charging connector, the authentication datum, wherein the verification comprises a blockchain authentication of the authentication datum; and enabling charging of the electric aircraft, at the charging connector and by the computing device, as a function of the verification of the authentication datum.
 2. The method of claim 1, wherein the computing device is a part of the charging connector.
 3. The method of claim 1, wherein receiving the authentication datum further comprises communicatively connecting the charging connector and the electric aircraft.
 4. The method of claim 1, wherein receiving the authentication datum further comprises electrically connecting a control pilot of the charging connector and the electric aircraft port.
 5. The method of claim 1, wherein the authentication datum comprises information on an identification of the electric aircraft.
 6. The method of claim 1, wherein the authentication datum comprises information on an identification of an owner of the electric aircraft.
 7. The method of claim 1, wherein the authentication datum comprises information on a recharging appointment of the electric aircraft.
 8. The method of claim 1, wherein the authentication datum includes a passcode.
 9. The method of claim 1, wherein verifying the authentication datum further comprises accessing a database.
 10. The method of claim 1, wherein enabling charging of the electric aircraft further comprises transmitting a control signal to the charging connector.
 11. A system for authentication of an electric aircraft for recharging, the system comprising: a charging connector, wherein the charging connector is configured to: receive an authentication datum from an electric aircraft; and mate with an electric aircraft port of the electric aircraft; and a computing device communicatively connected to the charging connector, wherein the computing device is configured to: verify the authentication datum, wherein the verification comprises a blockchain authentication of the authentication datum; and enable, at the charging connector, charging of the electric aircraft as a function of the verification of the authentication datum.
 12. The system of claim 11, wherein the computing device is a part of the charging connector.
 13. The system of claim 11, wherein the charging connector is configured to communicatively connect to the electric aircraft.
 14. The system of claim 11, wherein the charging connector further comprises a control pilot, and wherein the control pilot is configured to electrically connect to the electric aircraft port.
 15. The system of claim 11, wherein the authentication datum comprises information on an identification of the electric aircraft.
 16. The system of claim 11, wherein the authentication datum comprises information on an identification of an owner of the electric aircraft.
 17. The system of claim 11, wherein the authentication datum comprises information on a recharging appointment of the electric aircraft.
 18. The system of claim 11, wherein the authentication datum includes a passcode.
 19. The system of claim 11, wherein the computing device is further configured to verify the authentication datum by accessing a database.
 20. The system of claim 11, wherein the computing device is further configured to enable charging of the electric aircraft by transmitting a control signal to the charging connector. 